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Record W2034013771 · doi:10.1111/pcmr.12215

<i><scp>MITF</scp></i>E318K's effect on melanoma risk independent of, but modified by, other risk factors

2014· article· en· W2034013771 on OpenAlexaff
Marianne Berwick, Jamie MacArthur, Irene Orlow, Peter A. Kanetsky, Colin B. Begg, Li Luo, Anne S. Reiner, Ajay Sharma, Bruce K. Armstrong, Anne Kricker, Anne Ε. Cust, Loraine D. Marrett, Stephen B. Gruber, Hoda Anton‐Culver, Roberto Zanetti, Stefano Rosso, Richard P. Gallagher, Terence Dwyer, Alison Venn, Klaus J. Busam, Lynn From, Kirsten A. White, Nancy E. Thomas

Bibliographic record

VenuePigment Cell & Melanoma Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsSpinal Cord Injury BCWomen's College HospitalBC Cancer AgencyBC Cancer FoundationCancer Care Ontario
FundersNational Institute of Environmental Health SciencesNational Cancer Institute
KeywordsMicrophthalmia-associated transcription factorMelanomaMedicineOncologyCancer researchInternal medicineBiologyGeneticsTranscription factorGene

Abstract

fetched live from OpenAlex

A rare germline variant in the microphthalmia-associated transcription factor (MITF) gene, E318K, has been reported as associated with melanoma. We confirmed its independent association with melanoma [odds ratio (OR) 1.7, 95% confidence interval (CI) = 1.1, 2.7, P = 0.03]; adjusted for age, sex, center, age × sex interaction, pigmentation characteristics, family history of melanoma, and nevus density). In stratified analyses, carriage of MITF E318K was associated with melanoma more strongly in people with dark hair than fair hair (P for interaction, 0.03) and in those with no moles than some or many moles (P for interaction, <0.01). There was no evidence of interaction between MC1R 'red hair variants' and MITF E318K. Moreover, risk of melanoma among carriers with 'low risk' phenotypes was as great or greater than among those with 'at risk' phenotypes with few exceptions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.289
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2014
Admission routes1
Has abstractyes

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