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Juliette Commagere
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Juliette Commagere is a Los Angeles-based singer-songwriter who was formerly the lead singer and keytar player of the band Hello Stranger. In 2008 she began a solo career with the release of Queens Die Proudly.
Commagere has also performed with Maynard James Keenan of Tool's project Puscifer, The Bird and the Bee, Nick Lowe, Ry Cooder, Linda Perry and Liz Phair. She has opened for Air, Foo Fighters, The Bird and the Bee, Pete Yorn, Ry Cooder and Nick Lowe, and played the Latitude Festival with Bat for Lashes as well as co-headlined the 2nd annual Manimal Festival in Joshua Tree, CA with Warpaint, Edward Sharpe & the Magnetic Zeros and Hecuba.
Her solo work has been featured in numerous television shows and films including Private Practice, Emily Owens, M.D., Drop Dead Diva, Femme Fatales, The Power of Two, Good Dick and All the Boys Love Mandy Lane. In 2014 she did a cover of Night Ranger's power ballad "Sister Christian", which appeared in Grey's Anatomy.
She sang the female sections in Avenged Sevenfold's song "A Little Piece of Heaven" of their 2007 self-titled album. She has also sung on Taylor Hawkins's (of the Foo Fighters) side project Taylor Hawkins and the Coattail Riders album, releases by Puscifer, as well as on many Ry Cooder records including: Mambo Sinuendo, Chavez Ravine, I, Flathead, My Name Is Buddy, and Ibrahim Ferrer's Buenos Hermanos. Along with her husband Joachim Cooder she produced Carly Ritter's self-titled debut album on Vanguard Records in 2013.
Juliette's younger brother is singer/songwriter Robert Francis.
Her debut album, Queens Die Proudly, was released in October 2008 on the Aeronaut Records imprint. In early 2010, Juliette signed with Manimal Vinyl to release her second album titled The Procession. Her third album, Human, was released on September 17, 2013, on Aeronaut Records.
Contents
[hide]
1 Discography
2 Singles
3 Collaborations
4 External links
Discography[edit]
Hello Stranger (Aeronaut Records, July 25, 2006)
Queens Die Proudly (Aeronaut Records, October 28, 2008)
The Procession (Manimal Vinyl, September 24, 2010)
Human (Aeronaut Records, September 17, 2013)
Singles[edit]
"Eats from the Inside" (The Procession; June 14, 2010)
"Impact" (The Procession; December 2, 2010)
"Vampire (Puscifer Remix)" (Single only; January 14, 2014)
"Collide" (Human; March 11, 2014)
"Sister Christian" (Single only; April 8, 2014)
Collaborations[edit]
"Cold Moonlight" by Totally Radd (The Treble Alliance, November 14, 2006)
"A Little Piece of Heaven" by Avenged Sevenfold (Warner Bros. Records (U.S.)/WEA International (Worldwide), October 26, 2007)
"Fly and Fly" by The Sweet Hurt (The Sweet Hurt, June 13, 2014)
External links[edit]
Official Facebook
Official Myspace
New York Times article
Wikinews has related news: Bat for Lashes plays the Bowery Ballroom: an Interview with Natasha Khan
Manimal Vinyl Official Site
Manimal Vinyl at MySpace
Bat for Lashes at Discogs
Sarcastic Laist interview with an intern posing as Paul Beahan
Reviews of Manimal Festival 2008
Pitchforkmedia Review of Madonna Tribute
Pitchfork News Article on Upcoming tribute to The Cure
Spin Magazine Review of Madonna Tribute Record
Retrieved from "https://en.wikipedia.org/w/index.php?title=Juliette_Commagere&oldid=809241349"
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Sensitivity and specificity
From Wikipedia, the free encyclopedia
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This article may be too technical for most readers to understand. Please help improve it to make it understandable to non-experts, without removing the technical details. (June 2017) (Learn how and when to remove this template message)
Sensitivity and specificity
Sensitivity and specificity are statistical measures of the performance of a binary classification test, also known in statistics as classification function:
Sensitivity (also called the true positive rate, the recall, or probability of detection[1] in some fields) measures the proportion of positives that are correctly identified as such (e.g. the percentage of sick people who are correctly identified as having the condition).
Specificity (also called the true negative rate) measures the proportion of negatives that are correctly identified as such (e.g. the percentage of healthy people who are correctly identified as not having the condition).
Another way to understand in the context of medical tests is that sensitivity is the extent to which true positives are not missed/overlooked (so false negatives are few) and specificity is the extent to which positives really represent the condition of interest and not some other condition being mistaken for it (so false positives are few). Thus a highly sensitive test rarely overlooks a positive (for example, showing "nothing bad" despite something bad existing); a highly specific test rarely registers a positive for anything that is not the target of testing (for example, finding one bacterial species when another closely related one is the true target); and a test that is highly sensitive and highly specific does both, so it "rarely overlooks a thing that it is looking for" and it "rarely mistakes anything else for that thing." Because most medical tests do not have sensitivity and specificity values above 99%, "rarely" does not equate to certainty. But for practical reasons, tests with sensitivity and specificity values above 90% have high credibility, albeit usually no certainty, in differential diagnosis.
Sensitivity therefore quantifies the avoiding of false negatives, and specificity does the same for false positives. For any test, there is usually a trade-off between the measures – for instance, in airport security since testing of passengers is for potential threats to safety, scanners may be set to trigger alarms on low-risk items like belt buckles and keys (low specificity), in order to increase the probability of identifying dangerous objects and minimize the risk of missing objects that do pose a threat (high sensitivity). This trade-off can be represented graphically using a receiver operating characteristic curve. A perfect predictor would be described as 100% sensitive, meaning all sick individuals are correctly identified as sick, and 100% specific, meaning no healthy individuals are incorrectly identified as sick. In reality, however, any non-deterministic predictor will possess a minimum error bound known as the Bayes error rate.
Contents
[hide]
1 Definitions
1.1 Application to screening study
1.2 Confusion matrix
2 Sensitivity
3 Specificity
4 Graphical illustration
5 Medical examples
5.1 Misconceptions
5.2 Sensitivity index
6 Worked example
7 Estimation of errors in quoted sensitivity or specificity
8 Terminology in information retrieval
9 See also
10 References
11 Further reading
12 External links
Definitions[edit]
Terminology and derivations
from a confusion matrix
(number of) positive samples (P)
(number of) negative samples (N)
(number of) true positive (TP)
eqv. with hit
(number of) true negative (TN)
eqv. with correct rejection
(number of) false positive (FP)
eqv. with false alarm, Type I error
(number of) false negative (FN)
eqv. with miss, Type II error
sensitivity or true positive rate (TPR)
eqv. with hit rate, recall
T P R = T P / P = T P / ( T P + F N ) {\displaystyle {\mathit {TPR}}={\mathit {TP}}/P={\mathit {TP}}/({\mathit {TP}}+{\mathit {FN}})}
specificity (SPC) or true negative rate
S P C = T N / N = T N / ( T N + F P ) {\displaystyle {\mathit {SPC}}={\mathit {TN}}/N={\mathit {TN}}/({\mathit {TN}}+{\mathit {FP}})}
precision or positive predictive value (PPV)
P P V = T P / ( T P + F P ) {\displaystyle {\mathit {PPV}}={\mathit {TP}}/({\mathit {TP}}+{\mathit {FP}})}
negative predictive value (NPV)
N P V = T N / ( T N + F N ) {\displaystyle {\mathit {NPV}}={\mathit {TN}}/({\mathit {TN}}+{\mathit {FN}})}
fall-out or false positive rate (FPR)
F P R = F P / N = F P / ( F P + T N ) = 1 − S P C {\displaystyle {\mathit {FPR}}={\mathit {FP}}/N={\mathit {FP}}/({\mathit {FP}}+{\mathit {TN}})=1-{\mathit {SPC}}}
false negative rate (FNR)
F N R = F N / ( T P + F N ) = 1 − T P R {\displaystyle {\mathit {FNR}}={\mathit {FN}}/({\mathit {TP}}+{\mathit {FN}})=1-{\mathit {TPR}}}
false discovery rate (FDR)
F D R = F P / ( T P + F P ) = 1 − P P V {\displaystyle {\mathit {FDR}}={\mathit {FP}}/({\mathit {TP}}+{\mathit {FP}})=1-{\mathit {PPV}}}
accuracy (ACC)
A C C = ( T P + T N ) / ( T P + F P + F N + T N ) {\displaystyle {\mathit {ACC}}=({\mathit {TP}}+{\mathit {TN}})/({\mathit {TP}}+{\mathit {FP}}+{\mathit {FN}}+{\mathit {TN}})}
F1 score
is the harmonic mean of precision and sensitivity
F 1 = 2 T P / ( 2 T P + F P + F N ) {\displaystyle {\mathit {F1}}=2{\mathit {TP}}/(2{\mathit {TP}}+{\mathit {FP}}+{\mathit {FN}})}
Matthews correlation coefficient (MCC)
T P × T N − F P × F N ( T P + F P ) ( T P + F N ) ( T N + F P ) ( T N + F N ) {\displaystyle {\frac {{\mathit {TP}}\times {\mathit {TN}}-{\mathit {FP}}\times {\mathit {FN}}}{\sqrt {({\mathit {TP}}+{\mathit {FP}})({\mathit {TP}}+{\mathit {FN}})({\mathit {TN}}+{\mathit {FP}})({\mathit {TN}}+{\mathit {FN}})}}}}
Informedness
T P R + S P C − 1 {\displaystyle {\mathit {TPR}}+{\mathit {SPC}}-1}
Markedness
P P V + N P V − 1 {\displaystyle {\mathit {PPV}}+{\mathit {NPV}}-1}
Sources: Fawcett (2006) and Powers (2011).[2][3]
Application to screening study[edit]
Imagine a study evaluating a new test that screens people for a disease. Each person taking the test either has or does not have the disease. The test outcome can be positive (classifying the person as having the disease) or negative (classifying the person as not having the disease). The test results for each subject may or may not match the subject's actual status. In that setting:
True positive: Sick people correctly identified as sick
False positive: Healthy people incorrectly identified as sick
True negative: Healthy people correctly identified as healthy
False negative: Sick people incorrectly identified as healthy
In general, Positive = identified and negative = rejected. Therefore:
True positive = correctly identified
False positive = incorrectly identified
True negative = correctly rejected
False negative = incorrectly rejected
Confusion matrix[edit]
Let us consider a group with P positive instances and N negative instances of some condition. The four outcomes can be formulated in a 2×2 contingency table or confusion matrix, as follows:
True condition
Total population Condition positive Condition negative Prevalence = Σ Condition positive/Σ Total population Accuracy (ACC) = Σ True positive + Σ True negative/Σ Total population
Predicted
condition Predicted condition
positive True positive,
Power False positive,
Type I error Positive predictive value (PPV), Precision = Σ True positive/Σ Predicted condition positive False discovery rate (FDR) = Σ False positive/Σ Predicted condition positive
Predicted condition
negative False negative,
Type II error True negative False omission rate (FOR) = Σ False negative/Σ Predicted condition negative Negative predictive value (NPV) = Σ True negative/Σ Predicted condition negative
True positive rate (TPR), Recall, Sensitivity, probability of detection = Σ True positive/Σ Condition positive False positive rate (FPR), Fall-out, probability of false alarm = Σ False positive/Σ Condition negative Positive likelihood ratio (LR+) = TPR/FPR Diagnostic odds ratio (DOR) = LR+/LR− F1 score = 2/1/Recall + 1/Precision
False negative rate (FNR), Miss rate = Σ False negative/Σ Condition positive True negative rate (TNR), Specificity (SPC) = Σ True negative/Σ Condition negative Negative likelihood ratio (LR−) = FNR/TNR
Sensitivity[edit]
Sensitivity refers to the test's ability to correctly detect ill patients who do have the condition.[4] In the example of a medical test used to identify a disease, the sensitivity of the test is the proportion of people who test positive for the disease among those who have the disease. Mathematically, this can be expressed as:
sensitivity = number of true positives number of true positives + number of false negatives = number of true positives total number of sick individuals in population = probability of a positive test given that the patient has the disease {\displaystyle {\begin{aligned}{\text{sensitivity}}&={\frac {\text{number of true positives}}{{\text{number of true positives}}+{\text{number of false negatives}}}}\\[8pt]&={\frac {\text{number of true positives}}{\text{total number of sick individuals in population}}}\\[8pt]&={\text{probability of a positive test given that the patient has the disease}}\end{aligned}}}
A negative result in a test with high sensitivity is useful for ruling out disease.[4] A high sensitivity test is reliable when its result is negative, since it rarely misdiagnoses those who have the disease. A test with 100% sensitivity will recognize all patients with the disease by testing positive. A negative test result would definitively rule out presence of the disease in a patient.
A positive result in a test with high sensitivity is not useful for ruling in disease. Suppose a 'bogus' test kit is designed to show only one reading, positive. When used on diseased patients, all patients test positive, giving the test 100% sensitivity. However, sensitivity by definition does not take into account false positives. The bogus test also returns positive on all healthy patients, giving it a false positive rate of 100%, rendering it useless for detecting or "ruling in" the disease.
Sensitivity is not the same as the precision or positive predictive value (ratio of true positives to combined true and false positives), which is as much a statement about the proportion of actual positives in the population being tested as it is about the test.
The calculation of sensitivity does not take into account indeterminate test results. If a test cannot be repeated, indeterminate samples either should be excluded from the analysis (the number of exclusions should be stated when quoting sensitivity) or can be treated as false negatives (which gives the worst-case value for sensitivity and may therefore underestimate it).
Specificity[edit]
Specificity relates to the test's ability to correctly reject healthy patients without a condition. Consider the example of a medical test for diagnosing a disease. Specificity of a test is the proportion of healthy patients known not to have the disease, who will test negative for it. Mathematically, this can also be written as:
specificity = number of true negatives number of true negatives + number of false positives = number of true negatives total number of well individuals in population = probability of a negative test given that the patient is well {\displaystyle {\begin{aligned}{\text{specificity}}&={\frac {\text{number of true negatives}}{{\text{number of true negatives}}+{\text{number of false positives}}}}\\[8pt]&={\frac {\text{number of true negatives}}{\text{total number of well individuals in population}}}\\[8pt]&={\text{probability of a negative test given that the patient is well}}\end{aligned}}}
A positive result in a test with high specificity is useful for ruling in disease. The test rarely gives positive results in healthy patients. A test with 100% specificity will read negative, and accurately exclude disease from all healthy patients. A positive result signifies a high probability of the presence of disease.[5]
A test with a higher specificity has a lower type I error rate.
Graphical illustration[edit]
High sensitivity and low specificity
Low sensitivity and high specificity
Medical examples[edit]
In medical diagnosis, test sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas test specificity is the ability of the test to correctly identify those without the disease (true negative rate). If 100 patients known to have a disease were tested, and 43 test positive, then the test has 43% sensitivity. If 100 with no disease are tested and 96 return a negative result, then the test has 96% specificity. Sensitivity and specificity are prevalence-independent test characteristics, as their values are intrinsic to the test and do not depend on the disease prevalence in the population of interest.[6] Positive and negative predictive values, but not sensitivity or specificity, are values influenced by the prevalence of disease in the population that is being tested. These concepts are illustrated graphically in this applet Bayesian clinical diagnostic model which show the positive and negative predictive values as a function of the prevalence, the sensitivity and specificity.
Misconceptions[edit]
It is often claimed that a highly specific test is effective at ruling in a disease when positive, while a highly sensitive test is deemed effective at ruling out a disease when negative.[7][8] This has led to the widely used mnemonics SPIN and SNOUT, according to which a highly SPecific test, when Positive, rules IN disease (SP-P-IN), and a highly 'SeNsitive' test, when Negative rules OUT disease (SN-N-OUT). Both rules of thumb are, however, inferentially misleading, as the diagnostic power of any test is determined by both its sensitivity and its specificity.[9][10][11]
The tradeoff between Specificity and Sensitivity is explored in ROC analysis as a trade off between TPR and FPR (that is Recall and Fallout).[2] Giving them equal weight optimizes Informedness = Specificity+Sensitivity-1 = TPR-FPR, the magnitude of which gives the probability of an informed decision between the two classes (>0 represents appropriate use of information, 0 represents chance-level performance, <0 represents perverse use of information).[3]
Sensitivity index[edit]
The sensitivity index or d' (pronounced 'dee-prime') is a statistic used in signal detection theory. It provides the separation between the means of the signal and the noise distributions, compared against the standard deviation of the noise distribution. For normally distributed signal and noise with mean and standard deviations μ S {\displaystyle \mu _{S}} and σ S {\displaystyle \sigma _{S}} , and μ N {\displaystyle \mu _{N}} and σ N {\displaystyle \sigma _{N}} , respectively, d' is defined as:
d ′ = μ S − μ N 1 2 ( σ S 2 + σ N 2 ) {\displaystyle d'={\frac {\mu _{S}-\mu _{N}}{\sqrt {{\frac {1}{2}}(\sigma _{S}^{2}+\sigma _{N}^{2})}}}} [12]
An estimate of d' can be also found from measurements of the hit rate and false-alarm rate. It is calculated as:
d' = Z(hit rate) – Z(false alarm rate),[13]
where function Z(p), p ∈ [0,1], is the inverse of the cumulative Gaussian distribution.
d' is a dimensionless statistic. A higher d' indicates that the signal can be more readily detected.
Worked example[edit]
view
talk
edit
A worked example
A diagnostic test with sensitivity 67% and specificity 91% is applied to 2030 people to look for a disorder with a population prevalence of 1.48%
Patients with bowel cancer
(as confirmed on endoscopy)
Condition positive Condition negative
Fecal
occult
blood
screen
test
outcome Test
outcome
positive True positive
(TP) = 20 False positive
(FP) = 180 Positive predictive value
= TP / (TP + FP)
= 20 / (20 + 180)
= 10%
Test
outcome
negative False negative
(FN) = 10 True negative
(TN) = 1820 Negative predictive value
= TN / (FN + TN)
= 1820 / (10 + 1820)
≈ 99.5%
Sensitivity
= TP / (TP + FN)
= 20 / (20 + 10)
≈ 67%
Specificity
= TN / (FP + TN)
= 1820 / (180 + 1820)
= 91%
Related calculations
False positive rate (α) = type I error = 1 − specificity = FP / (FP + TN) = 180 / (180 + 1820) = 9%
False negative rate (β) = type II error = 1 − sensitivity = FN / (TP + FN) = 10 / (20 + 10) = 33%
Power = sensitivity = 1 − β
Likelihood ratio positive = sensitivity / (1 − specificity) = 0.67 / (1 − 0.91) = 7.4
Likelihood ratio negative = (1 − sensitivity) / specificity = (1 − 0.67) / 0.91 = 0.37
Hence with large numbers of false positives and few false negatives, a positive screen test is in itself poor at confirming the disorder (PPV = 10%) and further investigations must be undertaken; it did, however, correctly identify 66.7% of all cases (the sensitivity). However as a screening test, a negative result is very good at reassuring that a patient does not have the disorder (NPV = 99.5%) and at this initial screen correctly identifies 91% of those who do not have cancer (the specificity).
Estimation of errors in quoted sensitivity or specificity[edit]
Sensitivity and specificity values alone may be highly misleading. The 'worst-case' sensitivity or specificity must be calculated in order to avoid reliance on experiments with few results. For example, a particular test may easily show 100% sensitivity if tested against the gold standard four times, but a single additional test against the gold standard that gave a poor result would imply a sensitivity of only 80%. A common way to do this is to state the binomial proportion confidence interval, often calculated using a Wilson score interval.
Confidence intervals for sensitivity and specificity can be calculated, giving the range of values within which the correct value lies at a given confidence level (e.g., 95%).[14]
Terminology in information retrieval[edit]
In information retrieval, the positive predictive value is called precision, and sensitivity is called recall. Unlike the Specificity vs Sensitivity tradeoff, these measures are both independent of the number of true negatives, which is generally unknown and much larger than the actual numbers of relevant and retrieved documents. This assumption of very large numbers of true negatives versus positives is rare in other applications.[3]
The F-score can be used as a single measure of performance of the test for the positive class. The F-score is the harmonic mean of precision and recall:
F = 2 × precision × recall precision + recall {\displaystyle F=2\times {\frac {{\text{precision}}\times {\text{recall}}}{{\text{precision}}+{\text{recall}}}}}
In the traditional language of statistical hypothesis testing, the sensitivity of a test is called the statistical power of the test, although the word power in that context has a more general usage that is not applicable in the present context. A sensitive test will have fewer Type II errors.
See also[edit]
Science portal
Biology portal
Medicine portal
Brier score
Cumulative accuracy profile
False positive paradox
NCSS (statistical software) includes sensitivity and specificity analysis.
OpenEpi software program
Discrimination
Precision and recall
Statistical significance
Uncertainty coefficient, also called proficiency
Youden's J statistic
References[edit]
Jump up ^ "Detector Performance Analysis Using ROC Curves – MATLAB & Simulink Example". www.mathworks.com. Retrieved 11 August 2016.
^ Jump up to: a b Fawcett, Tom (2006). "An Introduction to ROC Analysis". Pattern Recognition Letters. 27 (8): 861–874. doi:10.1016/j.patrec.2005.10.010.
^ Jump up to: a b c Powers, David M W (2011). "Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness & Correlation" (PDF). Journal of Machine Learning Technologies. 2 (1): 37–63.
^ Jump up to: a b Altman, D. G.; Bland, J. M. (11 June 1994). "Statistics Notes: Diagnostic tests 1: sensitivity and specificity". BMJ. 308 (6943): 1552. doi:10.1136/bmj.308.6943.1552. PMC 2540489  . PMID 8019315 – via www.bmj.com.
Jump up ^ "SpPins and SnNouts". Centre for Evidence Based Medicine (CEBM). Retrieved 26 December 2013.
Jump up ^ Mangrulkar, Rajesh. "Diagnostic Reasoning I and II". Retrieved 24 January 2012.
Jump up ^ "Evidence-Based Diagnosis". Michigan State University.
Jump up ^ "Sensitivity and Specificity". Emory University Medical School Evidence Based Medicine course.
Jump up ^ Baron, JA (Apr–Jun 1994). "Too bad it isn't true...". Medical decision making : an international journal of the Society for Medical Decision Making. 14 (2): 107. doi:10.1177/0272989X9401400202. PMID 8028462.
Jump up ^ Boyko, EJ (Apr–Jun 1994). "Ruling out or ruling in disease with the most sensitive or specific diagnostic test: short cut or wrong turn?". Medical decision making : an international journal of the Society for Medical Decision Making. 14 (2): 175–179. doi:10.1177/0272989X9401400210. PMID 8028470.
Jump up ^ Pewsner, D; Battaglia, M; Minder, C; Marx, A; Bucher, HC; Egger, M (Jul 24, 2004). "Ruling a diagnosis in or out with "SpPIn" and "SnNOut": a note of caution". BMJ (Clinical research ed.). 329 (7459): 209–13. doi:10.1136/bmj.329.7459.209. PMC 487735  . PMID 15271832.
Jump up ^ Gale, SD; Perkel, DJ (Jan 20, 2010). "A basal ganglia pathway drives selective auditory responses in songbird dopaminergic neurons via disinhibition". The Journal of Neuroscience. 30 (3): 1027–1037. doi:10.1523/JNEUROSCI.3585-09.2010. PMC 2824341  . PMID 20089911.
Jump up ^ Macmillan, Neil A.; Creelman, C. Douglas (15 September 2004). Detection Theory: A User's Guide. Psychology Press. p. 7. ISBN 978-1-4106-1114-7.
Jump up ^ "Diagnostic test online calculator calculates sensitivity, specificity, likelihood ratios and predictive values from a 2x2 table – calculator of confidence intervals for predictive parameters". medcalc.org.
Further reading[edit]
Altman DG, Bland JM (1994). "Diagnostic tests. 1: Sensitivity and specificity". BMJ. 308 (6943): 1552. doi:10.1136/bmj.308.6943.1552. PMC 2540489  . PMID 8019315.
Loong T (2003). "Understanding sensitivity and specificity with the right side of the brain". BMJ. 327 (7417): 716–719. doi:10.1136/bmj.327.7417.716. PMC 200804  . PMID 14512479.
External links[edit]
UIC Calculator
Vassar College's Sensitivity/Specificity Calculator
MedCalc Free Online Calculator
Bayesian clinical diagnostic model applet
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(EBM I to II-1; A to B)
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(EBM II-2 to II-3; B to C)
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methods
occurrence: Incidence (Cumulative incidence)
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association: absolute (Absolute risk reduction, Attributable risk, Attributable risk percent)
relative (Relative risk, Odds ratio, Hazard ratio)
other: Clinical endpoint
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Cole Turner
From Wikipedia, the free encyclopedia
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Cole Turner
Charmed character
Julian McMahon as Cole Turner
First appearance
October 5, 2000
(episode 3.01; "The Honeymoon's Over")
Last appearance
April 10, 2005
(episode 7.16; "The Seven Year Witch")
Created by
Brad Kern
Portrayed by
Julian McMahon (human form)
Michael Bailey Smith (demon form)
Information
Aliases
Belthazor and The Source of All Evil
Species
Human
Demon
Occupation
Lawyer
Family
Benjamin Turner
(father; deceased)
Elizabeth Turner
(mother; deceased)
Penny 'Grams' Halliwell
(ex-grandmother-in-law; deceased)
Allen Halliwell
(ex-grandfather-in-law; deceased)
Patricia 'Patty' Halliwell
(ex-mother-in-law; deceased)
Victor Bennett
(ex-father-in-law)
Prue Halliwell
(ex-sister-in-law; deceased)
Piper Halliwell
(ex-sister-in-law)
Paige Matthews
(ex-sister-in-law)
Leo Wyatt
(ex-brother-in-law)
Spouse(s)
Phoebe Halliwell
(ex-wife)
Cole Turner is a fictional character on the WB television series Charmed, portrayed by series regular Julian McMahon between seasons three and five. McMahon returned for a guest appearance in the show's seventh season, for its 150th episode. Charmed is a series which focuses on three good witches, the prophesied "Charmed Ones", sisters who battle the forces of evil. Cole is an adversary-turned-ally of the sisters introduced in the third season and a love interest of main character Phoebe Halliwell, portrayed by Alyssa Milano. Like the show's main characters, Cole also possessed a number of magical abilities; the most commonly used were the power to teleport and the power to throw projective energy balls which could stun or kill.
Within the series' narrative, Cole is half-human and half-demon by blood, and better known to the demonic world for over a hundred years as the legendary demonic assassin Belthazor. Cole is dispatched by the Source of all Evil himself to kill the Charmed Ones only to fall in love with then-youngest sister Phoebe, renounce evil and become a close ally of the Charmed Ones. Though Cole eventually completely rids himself of his demonic nature, and marries Phoebe in the fourth season, he never gains the trust of new youngest sister Paige (Rose McGowan).
As part of his storyline, the character later returns to evil after unwillingly becoming the new Source. As the Source, Cole is eventually vanquished by the Charmed Ones, only to come back from death itself in his attempts to win Phoebe back. By this point he is one of the most powerful beings to ever exist. Driven insane, Cole is, through his own doing, once again killed by the sisters in the fifth season. When the character returns for a guest appearance in the seventh season, it is unclear what kind of being he is, but he states that he is caught somewhere between life and death, atoning for his sins.
Contents
[hide]
1 Character arc
1.1 Season three (2000–01)
1.2 Season four (2001–02)
1.3 Season five (2002–03) and other appearances
2 Analysis
3 Influence
4 References
Character arc[edit]
Season three (2000–01)[edit]
Cole Turner makes his first appearance in the third-season (2000–01) premiere episode, "The Honeymoon's Over". Charmed Ones Phoebe (Alyssa Milano) and Prue (Shannen Doherty) run into Assistant District Attorney Cole Turner at the site where they killed a demon, and cover their tracks. Over the course of the episode, it becomes apparent to the audience that Cole is himself a very powerful demon, pursuing Phoebe romantically and deceiving the sisters as to his true nature in order to finally kill them.
In "Power Outage", Cole's superiors, the demonic Triad, learn that he may have developed genuine romantic feelings for Phoebe; Cole responds by killing them, forcing him into hiding. Meanwhile, the sisters acquire a target in the red-and-black-skinned demon Belthazor (Michael Bailey Smith). In "Sleuthing with the Enemy", the Charmed Ones discovers Cole and Belthazor are one and the same, but when Cole convinces Phoebe that he, being half human, truly loves her, she fakes his death so that her sisters Piper (Holly Marie Combs) and Prue will not hunt for him.
When Cole re-emerges, causing a rift between Phoebe and her sisters, he attempts to re-ingratiate himself with his demonic peers, the Brotherhood of the Thorn, as the sisters' double agent. When Prue and Piper are both killed following a successful mission by the Source's assassin Shax (Michael Bailey Smith) in the season finale "All Hell Breaks Loose", Cole begs the Source (again, Michael Bailey Smith) to turn back time and prevent the exposure of magic. The Source agrees on the condition that Phoebe remain in the Underworld under his command, though he secretly orders her to be killed. Shax attacks the Halliwell Manor once more after time is reversed, but this time Leo (Brian Krause), Piper's husband who is also the sisters' guardian angel (whitelighter) is not available to heal either Piper or Prue, who lie gravely wounded.
Season four (2001–02)[edit]
The season four premiere "Charmed Again" reveals Leo arrived in time to heal Piper, but Prue died of her injuries, reflecting Doherty's departure from the series. Leo assisted Phoebe to escape the Underworld, absconding on the Source's deal. With Prue dead, the sisters are no longer the Charmed Ones, and Cole does what he can to assist Phoebe and Piper from Shax's continued attacks. Piper and Phoebe regain their full abilities—becoming Charmed Ones once again—when they discover their younger half-sister, Paige Matthews (Rose McGowan), alongside whom they finally destroy Shax.
In "Black as Cole", Cole proposes to Phoebe whilst they vanquish a low level demon. Later they find that Sykes has been mimicking Belthazor and in a bid to vanquish him Cole takes on his demonic form but has Phoebe create a potion to kill his demonic half if he can not change back. Before he can change back, a woman looking to revenge his killing of her love picks up the potion and throws it at him, causing Belthazor to die. In "Lost and Bound", Paige gets Cole a job as a legal aid lawyer. However he can't control his emotions and soon quits but not before the landlord who he was arguing with agrees to put the heating back on.
In "Charmed and Dangerous", the Source (Peter Woodward) breaks an aged old agreement and consumes the hollow. The Seer (Debbi Morgan) tricks Cole into consuming the hollow which allows him to assist the Charmed Ones in vanquishing the physical version of the Source. It is revealed that the Seer tricked Cole into absorbing the old Source's power, eventually causing him to become the new Source of Evil in "The Three Faces of Phoebe". An older version of Phoebe has turned bitter because of what he has done and warns her to save herself and states that they never got married but she can't help but think what might have been. Present-day Phoebe asks him if he is hiding anything; he says he is not.
The Source takes over Cole completely in "Marry-Go-Round". The Seer warns him that marrying Phoebe would be the worst thing possible as they would have a son, the most powerful magical creature ever, who would be on the side of good, following the Charmed Ones' destiny. She tells him the only way the child will grow up evil is if Cole marries Phoebe in a dark ceremony. As the Source, he puts a spell on the Charmed Ones which makes Phoebe spotty and Piper and Paige over sleep. Paige and Phoebe argue as the latter suspects the former of trying to disrupt the wedding, having already made a mistake with the dress. When Paige tries to make an amends with Phoebe's spots it causes her to become invisible.
Suspecting evil magic to be involved, the sisters try and reverse it without success but pass the invisibility on to Paige. Cole asks the Seer to send a Lazarus demon (who she summoned to lure Phoebe to a cemetery for the purposes of a dark ceremony) to attack at the wedding which causes Phoebe to call it off, thus reversing the magic on her, which had been switched to Paige. When the Charmed Ones question the demon, he accuses Cole of betraying him and tells them that he sent him to attack them. But before he can out Cole as the Source, Cole vanquishes him and pretends to be the Seer before teleporting and pretending to be unconscious after she attacked him. Cole marries Phoebe in a dark wedding at the end of the episode, without her suspecting drinking her blood when a throne pricks her with the ceremony held at night with a dark priest.
Cole pretends to be the perfect husband by sending Leo and Piper on honeymoon to Hawaii and buying expensive gifts such as a new car in "The Fifth Halliwheel". Paige begins to suspect that Cole is a demon again especially when she catches Cole using powers on an innocent but is not sure of what she has seen. Cole as Leo calms Paige's fears before sending the power broker demon who had already gone after the innocent after her. The Seer also puts in a plan to make Phoebe pregnant using the full moon and a tonic. The Seer and Cole create a tonic which will ensure that the child is evil. From taking the tonic, the child will take over Phoebe's body and ensure that she remains by his side when she finds out that he is the Source. Phoebe eventually takes the tonic laced with chocolate to make the plan work.
In "Bite Me" different factions have tried to become ruler of the Underworld so Cole tries to make them all work together to beat good. However one of the leaders encourages a group of vampires to rise up and rebel, which they do so after Cole refuses to listen to them. He almost gets exposed by Paige when she orbs in his home but he quickly covers this up by saying he has a migraine, hence why the blinds were down. The vampires try to turn Paige into one to get the other sisters and then overthrow the Source and become the new leaders. To keep himself on top, Cole kills the Queen after Phoebe and Piper inadvertently tell him what to do. Phoebe later discovers that she is pregnant before informing him in "We're Off to See the Wizard."
Cole tries to give up the Source to the Wizard after his human side becomes strong and Phoebe learns through a premonition that he is a demon again. But before the ritual is complete, the Seer, who has manipulated Phoebe, interrupts and vanquishes the Wizard. Cole is crowned the new Source with Phoebe as his Queen. Cole faces a coup in "Long Live the Queen" when Phoebe stops the killing of an innocent. Cole demands she make a choice. Phoebe later learns from the Seer and Cole that the tonic they were giving her was turning her evil. Phoebe eventually sides with her sisters and before Cole can destroy them she traps him in a crystal cage which allows the Charmed Ones to vanquish him.
In the season finale "Witch Way Now?", Phoebe discovers Cole is able to linger in the Demonic Wasteland, where vanquished demons go, because of his human soul. Phoebe visits him there, insisting to him that he move on to his afterlife. After she leaves, he accidentally discovers he can acquire the powers of other demons vanquished there. He becomes powerful enough to kill the beast that consumes the essence of those vanquished there and, finally, to escape. Once back in the real world, he saves the sisters' lives from a witch hunter.
Season five (2002–03) and other appearances[edit]
In the season-five premiere "A Witch's Tail", Cole returns with numerous new abilities, making him more powerful than ever. Though he still loves Phoebe, she wants to move on from him and is frustrated by his attempts to win her back. In "Siren Song," he saves the life of a young future whitelighter named Melissa in a failed attempt to impress Phoebe. When he tries to confront the demonic Siren the sisters are pursuing, the Siren puts him under her control. Under this influence, he tries to strangle Phoebe to death before the Siren is ultimately vanquished, and Phoebe nearly dies. As a result, Cole finally understands the threat he poses to Phoebe and promises to stop using his powers, but succumbs to temptation and kills again when confronted by a sleazy landlord.
In "Sympathy for the Demon", Cole is taunted by the spirit of the demon Barbas (Billy Drago), who convinces him to use a power-stripping potion, inadvertently granting Barbas his powers and a corporeal form. To stop the threat of Barbas or anyone else possessing Cole's powers, Paige strips Barbas of Cole's powers and Cole takes them back. The sisters, however, fear that these abilities will make him evil again. In "Sam, I Am", Cole misuses his abilities and incinerates two robbers/murderers, and is later visited by two mysterious beings who identify themselves as Avatars. Neither good or evil, the Avatars offer Cole the opportunity to join their ranks and enjoy their powers; he refuses.
Instead, Cole tries to provoke the sisters to kill him by sending an assassin after them, knowing that they will be able to recover thanks to their recent contact with Paige's father, whitelighter Sam Wilder (Scott Jaeck). He is distraught to learn he cannot be killed, and is pushed over the edge into insanity. Cole reverts to malevolent means of winning Phoebe back, striking at the Charmed Ones in various underhand ways over several episodes. In Charmed's 100th episode "Centennial Charmed", Cole accepts the Avatars' offer and uses their powers to create an alternate reality where Piper and Phoebe never met Paige, who was instead killed by the Source before the Elders discovered her. In the new reality, Cole is once again Belthazor and no longer indestructible. He acts as the right-hand man of the Source and owns Halliwell Manor with Phoebe, but they are unhappy together. Paige however is accidentally brought along from the real world and teams up with Piper and Leo to destroy Cole. After convincing Phoebe to join their side, the Charmed Ones vanquish Cole for good.
Cole makes a guest appearance in the 150th episode, "The Seven Year Witch", in season seven; Piper's disembodied spirit receives advice from Cole, who claims to be in limbo atoning for his sins. However, it is later revealed that Cole, watching over the sisters, orchestrated Piper's illness and sent Phoebe's short-lived boyfriend Drake (Billy Zane) to her, all so that Phoebe could learn to believe in love again. However he also did this to get Piper and Leo back together so that they could be a beacon for Phoebe not to give up on love and turn into the bitter old woman as seen in "The Three Faces of Phoebe". In 2010, Cole returned in the Charmed Season 9 comic book series. This time he has a minor role and only supporting in the spirit realm with Prue.
Analysis[edit]
As a lawyer and a demon, one writer notes that Cole is part of the same "corporate" metaphor as the Wolfram & Hart firm in the television series Angel.[1]
Influence[edit]
The erotic romance novels and novellas of Jennifer Dunne feature a heroine "obsessed" with Julian McMahon's portrayal of Cole in her book Dancing in the Dark.[2]
References[edit]
Jump up ^ Day, Peter (2006). "Piercing the corporate veil". Vampires: myths and metaphors of enduring evil. Editions Rodopi B.V. ISBN 90-420-1669-8.
Jump up ^ Dunne, Jennifer (2005). "Will the Real Phoebe Please Stand up". In Jennifer Crusie. Totally Charmed: Demons, Whitelighters and the Power of Three. BenBella Books. ISBN 1-932100-60-1.
[hide]
v
t
e
Charmed
Awards and nominations
Series
Episodes
Season 1
2
3
4
5
6
7
8
Comics and novels and short stories
Season 9
10
Characters
Prue Halliwell
Piper Halliwell
Phoebe Halliwell
Paige Matthews
Darryl Morris
Leo Wyatt
Cole Turner
Billie Jenkins
Coop
Henry Mitchell
Kyra
Barbas
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text:
As You Were (Liam Gallagher album)
From Wikipedia, the free encyclopedia
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As You Were
Studio album by Liam Gallagher
Released
6 October 2017
Recorded
2016–2017
Genre
Britpop[1]
Length
44:43
Label
Warner Bros.
Producer
Greg Kurstin
Dan Grech-Marguerat
Andrew Wyatt
Singles from As You Were
"Wall of Glass"
Released: 1 June 2017
"Chinatown"
Released: 30 June 2017
"For What It's Worth"
Released: 10 August 2017
"Greedy Soul"
Released: 27 September 2017
"Come Back to Me"
Released: 23 November 2017
As You Were is the debut studio album by English singer and songwriter Liam Gallagher. It was released on 6 October 2017 by Warner Bros. Records.[2] The album debuted at number one in the UK, outselling the rest of the top 10 of the UK Albums Chart combined and achieving gold certification in its first week. It also achieved the highest single-week vinyl sales in 20 years, with 16,000.[3]
Contents
[hide]
1 Background
2 Critical reception
2.1 Accolades
3 Commercial performance
4 Track listing
5 Personnel
6 Charts
6.1 Weekly charts
6.2 Year-end charts
7 Certifications
8 References
Background[edit]
The album was announced in June 2017 with the release of the single "Wall of Glass". Gallagher also revealed that he would launch his first solo tour of the United States and Canada to support the album's release.[4] The album's title comes from the sign-off Gallagher typically uses for his Twitter posts.[5] Gallagher worked with producers Greg Kurstin, Andrew Wyatt and Dan Grech-Marguerat on the album, with Kurstin producing the tracks "Wall of Glass", "Paper Crown", "Come Back to Me", and "Doesn't Have to Be That Way", Wyatt producing "Chinatown", and Grech-Marguerat producing the remaining tracks.[6]
Critical reception[edit]
Professional ratings
Aggregate scores
Source
Rating
Metacritic 71/100[7]
Review scores
Source
Rating
AllMusic [8]
The A.V. Club B+[9]
The Daily Telegraph [10]
The Guardian [11]
Mojo [12]
NME [13]
Pitchfork 4.9/10[14]
Q [15]
Rolling Stone [1]
Uncut 7/10[16]
As You Were received generally positive reviews from critics at Metacritic, which assigns a normalised rating out of 100 to reviews from mainstream publications, the album received an average score of 71, based on 24 reviews.
Stephen Thomas Erlewine from AllMusic was highly positive about the record in his four-star review, saying, "As You Were doesn't sound retro even though it is, in essence, a throwback to a throwback -- a re-articulation of Liam's '90s obsession with the '60s. That production does Gallagher a favor but so does Kurstin's presence as a co-songwriter, helping to rein in Liam's wandering ear and sharpen his melodies. Ranging from the icy onslaught of "Wall of Glass" to the stark swirl of "Chinatown" this is his best record in nearly a decade, and they add up to an album that illustrates exactly who Liam Gallagher is as an artist. Now in his middle age, he's a richer, nuanced singer than he was during Oasis's heyday, yet he's retained his charisma and, unlike his brother, he favors color and fire in his records, elements that not only enhance this fine collection of songs but make this the best post-Oasis album from either Gallagher to date."[8] Halina Watts from the Daily Mirror was also very positive towards the record, scoring the album five stars and saying, "'As You Were' is the legendary rocker at his very best" and that the album was "well worth the wait". She went onto describe "Chinatown" as a "catchy uplifting poem to the capital" and "For What It's Worth" and "Paper Crown" as "fantastic ballads". Watts rounded off the review by saying, "Bring on album two".[17]
Accolades[edit]
Publication
Accolade
Year
Rank
Ref.
Rough Trade Albums of the Year
2017
32
[18]
Commercial performance[edit]
As You Were sold 103,000 units in its first week in the United Kingdom.[3] It is the ninth-fastest selling debut of the decade within the nation.[19] In the United States, it opened at number 30 on the Billboard 200 with 15,000 album-equivalent units, including 14,000 traditional sales.[20]
Track listing[edit]
The album was released in numerous formats, from digital versions to vinyl, CD, and a "special box set" that includes a colorised vinyl record, an "exclusive seven-inch, hardback book and an art print by Klaus Voormann, the artist behind the Beatles' Revolver".[2] The track listing was revealed by Gallagher with the release of the album's second single "Chinatown".[21][22]
Standard edition
No.
Title
Writer(s)
Producer(s)
Length
1. "Wall of Glass"
Liam Gallagher
Greg Kurstin
Andrew Wyatt
Michael Tighe
Andrew Sidney Fox
Kurstin 3:43
2. "Bold" Gallagher
Dan Grech-Marguerat
Iain Archer[a]
3:59
3. "Greedy Soul" Gallagher Grech-Marguerat 3:34
4. "Paper Crown"
Wyatt
Tighe
Kurstin 3:28
5. "For What It's Worth"
Gallagher
Simon Jons
Grech-Marguerat 4:11
6. "When I'm in Need"
Gallagher
Archer
Grech-Marguerat
Archer[a]
4:18
7. "You Better Run" Gallagher Grech-Marguerat 3:24
8. "I Get By" Gallagher Grech-Marguerat 3:09
9. "Chinatown"
Wyatt
Tighe
Wyatt 3:20
10. "Come Back to Me"
Gallagher
Kurstin
Wyatt
Kurstin 3:21
11. "Universal Gleam" Gallagher Grech-Marguerat 4:07
12. "I've All I Need" Gallagher Grech-Marguerat 4:09
Total length: 44:43
[show]Deluxe edition bonus tracks
No.
Title
Writer(s)
Producer(s)
Length
13. "Doesn't Have to Be That Way"
Gallagher
Kurstin
Wyatt
Kurstin 3:58
14. "All My People / All Mankind" Gallagher Grech-Marguerat 3:55
15. "I Never Wanna Be Like You" Gallagher
Grech-Marguerat
Dan McDougall[b]
3:51
Total length: 56:27
[show]Japanese edition bonus tracks
No.
Title
Length
16. "For What It's Worth" (live at Air Studios) 4:13
17. "Greedy Soul" (live at Air Studios) 3:33
18. "Paper Crown" (live at Air Studios) 3:35
Total length: 1:07:48
Notes
^a signifies original song production.
^b signifies original demo production.
Personnel[edit]
Credits adapted from liner notes.
Musicians
Liam Gallagher – lead vocals (all tracks), acoustic guitar (tracks 3, 7, 11, 12, 14, 15)
Greg Kurstin – bass, drums, acoustic guitar, electric guitar, harmonica, percussion, mellotron, piano, organ, tanpura (tracks 1, 4, 10, 13)
Dan Grech-Marguerat – programming (tracks 2, 3, 5-8, 11, 12, 14, 15)
Davey Badiuk – programming (tracks 2, 3, 11, 12, 14)
Mike Moore – electric guitar (tracks 2, 3, 5-8, 11-13, 15), bass (track 5)
Dan McDougall – drums, bass, acoustic guitar, electric guitar, keyboards (tracks 2-9, 11, 12, 14, 15)
Martin Slattery – keyboards, saxophone (tracks 2, 3, 5-7, 11, 12, 14)
Ben Edwards – trumpet (tracks 3, 6-8, 11)
Mark Brown – saxophone (tracks 3, 6-8, 11)
Mike Kearsey – trombone (tracks 3, 6-8, 11)
Sally Herbert – violin, string arrangement (tracks 2, 5, 6, 11, 14), brass arrangement (tracks 3, 6-8, 11)
Ian Burdge – cello (tracks 2, 5, 6, 11, 14)
Rachel Robson – viola (tracks 5, 6, 11, 14)
Tom Pigott Smith – violin (tracks 6, 11, 14)
Andrew Wyatt – acoustic guitar (track 4), drum programming, piano, bass, synth, additional guitar, production (track 9), backing vocals (track 1)
Drew McConnell – bass (track 8)
Jay Mehler – acoustic guitar, electric guitar (track 8)
Christian Madden – keyboards (track 8)
Michael Tighe – acoustic guitar (track 9)
Bridget Sarai – backing vocals (track 1)
Vicky Akintola – backing vocals (2, 3, 6, 7, 11)
Production
Greg Kurstin – production, engineering (tracks 1, 4, 10, 13), mixing (track 10)
Dan Grech-Marguerat – production, engineering (tracks 2, 3, 5-8, 11, 12, 14, 15), mixing (track 15)
Andrew Wyatt – production (track 9)
Iain Archer – original song production (tracks 2, 6)
Dan McDougall – original demo production (track 15)
Alex Pasco – engineering (tracks 1, 4, 10, 13)
Julian Burg – engineering (tracks 1, 4, 10, 13)
Ben Mclusky – engineering (track 9), engineering assistance (tracks 2, 3, 5-7, 11, 12, 14, 15)
Joseph Rogers – engineering (track 9)
Joe Rodgers – engineering (track 15)
Joel Davies – engineering assistance (tracks 2, 3, 5-8, 11, 12, 14, 15)
Charles Haydon Hicks – engineering assistance (tracks 2, 3, 5-8, 11, 12, 14, 15)
Matt Mysko – engineering assistance (track 8)
Mark "Spike" Stent – mixing (tracks 1-9, 11-14)
Richard Woodcraft – brass section recording (track 11)
Julian Simmons – brass section recording (track 11)
Brian Lucey – mastering (all tracks)
Design
Hedi Slimane – cover shot, photography
Liam Gallagher – art direction, design
Richard Welland – art direction, design
Pixie Higson – photography commissioning
Charts[edit]
Weekly charts[edit]
Chart (2017)
Peak
position
Australian Albums (ARIA)[23]
9
Austrian Albums (Ö3 Austria)[24]
12
Belgian Albums (Ultratop Flanders)[25]
13
Belgian Albums (Ultratop Wallonia)[26]
21
Canadian Albums (Billboard)[27]
28
Dutch Albums (MegaCharts)[28]
15
Finnish Albums (Suomen virallinen lista)[29]
22
French Albums (SNEP)[30]
24
German Albums (Offizielle Top 100)[31]
14
Hungarian Albums (MAHASZ)[32]
16
Irish Albums (IRMA)[33]
1
Italian Albums (FIMI)[34]
4
Japanese Albums (Oricon)[35]
10
New Zealand Albums (RMNZ)[36]
13
Scottish Albums (OCC)[37]
1
South Korean International Albums (Gaon)[38]
1
Spanish Albums (PROMUSICAE)[39]
4
Swedish Albums (Sverigetopplistan)[40]
23
Swiss Albums (Schweizer Hitparade)[41]
4
UK Albums (OCC)[42]
1
US Billboard 200[43]
30
US Top Rock Albums (Billboard)[44]
5
Year-end charts[edit]
Chart (2017)
Position
UK Albums (OCC)[45]
9
Certifications[edit]
Region
Certification
Certified units/Sales
United Kingdom (BPI)[46]
Gold 100,000^
^shipments figures based on certification alone
References[edit]
^ Jump up to: a b Fricke, David (6 October 2017). "Liam Gallagher: As You Were". Rolling Stone. Retrieved 6 October 2017.
^ Jump up to: a b Daniel Kreps (23 June 2017). "Liam Gallagher Announces New LP 'As You Were,' First Solo U.S. Tour". Rolling Stone. Retrieved 1 July 2017.
^ Jump up to: a b White, Jack (13 October 2017). "Liam Gallagher's As You Were charges in at Number 1 on the Official Albums Chart and sets new vinyl record". Official Charts Company. Retrieved 14 October 2017.
Jump up ^ Noah Yoo and Jazz Monroe (23 June 2017). "Liam Gallagher Announces Tour, Details New Album As You Were". Pitchfork. Retrieved 1 July 2017.
Jump up ^ Anna Gaca (26 May 2017). "Liam Gallagher Announces Solo Album As You Were, Manchester Benefit Concert". Spin. Retrieved 1 July 2017.
Jump up ^ Ryan Reed (5 July 2017). "Watch Liam Gallagher Wander Through London in 'Chinatown' Video". Rolling Stone. Retrieved 5 July 2017.
Jump up ^ "Reviews and Tracks for As You Were by Liam Gallagher". Metacritic. Retrieved 10 October 2017.
^ Jump up to: a b Erlewine, Stephen Thomas. "As You Were – Liam Gallagher". AllMusic. Retrieved 3 October 2017.
Jump up ^ Ihnat, Gwen (7 October 2017). "Liam Gallagher, As You Were". The A.V. Club. Retrieved 7 October 2017.
Jump up ^ McCormick, Neil (5 October 2017). "Liam Gallagher, As You Were, review: as fresh and surprising as he endlessly boasted it would be". The Daily Telegraph. Retrieved 5 October 2017.
Jump up ^ Petridis, Alexis (5 October 2017). "Liam Gallagher: As You Were review – motormouth meets the Beatles, again". The Guardian. Retrieved 6 October 2017.
Jump up ^ Perry, Andrew (November 2017). "I should solo!". Mojo (288): 95.
Jump up ^ Cooper, Leonie (5 October 2017). "Liam Gallagher – 'As You Were' Review". NME. Retrieved 5 October 2017.
Jump up ^ Snapes, Laura (5 October 2017). "Liam Gallagher: As You Were". Pitchfork. Retrieved 5 October 2017.
Jump up ^ Moody, Paul (November 2017). "Comeback King". Q (378): 102.
Jump up ^ Staunton, Terry (November 2017). "Liam Gallagher: As You Were". Uncut (246): 28.
Jump up ^ Watts, Halina (7 October 2017). "Liam Gallagher wants to 'meet up and hug it out' with brother Noel: "Enough is enough now"". Daily Mirror. Retrieved 13 October 2017.
Jump up ^ "Albums of the Year". Rough Trade. November 14, 2017. Retrieved November 14, 2017.
Jump up ^ "The fastest-selling debut albums of the decade so far". Official Charts Company. Retrieved 14 October 2017.
Jump up ^ Caulfield, Keith (20 October 2017). "Billboard 200 Chart Moves: Stone Temple Pilots' 'Core' Reissue Hits Top 40". Billboard. Retrieved 22 October 2017.
Jump up ^ Nick Levine (29 June 2017). "Liam Gallagher unveils full 'As You Were' album tracklist". NME. Retrieved 1 July 2017.
Jump up ^ Daniel Kreps (30 June 2017). "Hear Liam Gallagher's Tender New Solo Song 'Chinatown'". Rolling Stone. Retrieved 1 July 2017.
Jump up ^ "Australiancharts.com – Liam Gallagher – As You Were". Hung Medien. Retrieved 14 October 2017.
Jump up ^ "Austriancharts.at – Liam Gallagher – As You Were" (in German). Hung Medien. Retrieved 18 October 2017.
Jump up ^ "Ultratop.be – Liam Gallagher – As You Were" (in Dutch). Hung Medien. Retrieved 13 October 2017.
Jump up ^ "Ultratop.be – Liam Gallagher – As You Were" (in French). Hung Medien. Retrieved 13 October 2017.
Jump up ^ "On The Charts: October 15, 2017". FYIMusicNews. Retrieved 17 October 2017.
Jump up ^ "Dutchcharts.nl – Liam Gallagher – As You Were" (in Dutch). Hung Medien. Retrieved 13 October 2017.
Jump up ^ "Liam Gallagher: As You Were" (in Finnish). Musiikkituottajat – IFPI Finland. Retrieved 15 October 2017.
Jump up ^ "Le Top de la semaine : Top Albums – SNEP (Week 41, 2017)". Syndicat National de l'Édition Phonographique. Retrieved 17 October 2017.
Jump up ^ "Offiziellecharts.de – Liam Gallagher – As You Were" (in German). GfK Entertainment Charts. Retrieved 13 October 2017.
Jump up ^ "Top 40 album-, DVD- és válogatáslemez-lista". MAHASZ. Retrieved 20 October 2017.
Jump up ^ "Irish Albums Chart: 13 October 2017". Irish Recorded Music Association. Retrieved 14 October 2017.
Jump up ^ "Album – Classifica settimanale WK 41 (dal 2017-10-06 al 2017-10-12)" (in Italian). Federazione Industria Musicale Italiana. Retrieved 14 October 2017.
Jump up ^ "リアム・ギャラガー" (in Japanese). Oricon. 13 October 2017. Retrieved 13 October 2017.
Jump up ^ "Charts.org.nz – Liam Gallagher – As You Were". Hung Medien. Retrieved 13 October 2017.
Jump up ^ "Official Scottish Albums Chart Top 100". Official Charts Company. Retrieved 14 October 2017.
Jump up ^ "2017년 41주차 Album Chart" (in Korean). Gaon Music Chart. Retrieved 19 October 2017.
Jump up ^ "Top 100 Albumes — Semana 41: del 06.10.2017 al 12.10.2017" (in Spanish). Productores de Música de España. Retrieved 18 October 2017.
Jump up ^ "Swedishcharts.com – Liam Gallagher – As You Were". Hung Medien. Retrieved 13 October 2017.
Jump up ^ "Swisscharts.com – Liam Gallagher – As You Were". Hung Medien. Retrieved 18 October 2017.
Jump up ^ "Official Albums Chart Top 100". Official Charts Company. Retrieved 14 October 2017.
Jump up ^ "Liam Gallagher Chart History". Billboard. Retrieved 17 October 2017.
Jump up ^ "Liam Gallagher Chart History". Billboard. Retrieved 17 October 2017.
Jump up ^ White, Jack (3 January 2018). "The Top 40 biggest albums of 2017 on the Official Chart". Official Charts Company. Retrieved 3 January 2018.
Jump up ^ "British album certifications – Liam Gallagher – As You Were". British Phonographic Industry. Retrieved 13 October 2017. Enter As You Were in the search field and then press Enter.
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