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Record W2399447400 · doi:10.21037/atm.2016.04.19

From genes to chronotypes: the influence of circadian clock genes on our daily patterns of sleep and wakefulness

2016· article· en· W2399447400 on OpenAlexafffund
Michael Verwey, Shimon Amir

Bibliographic record

VenueAnnals of Translational Medicine · 2016
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsMontreal Clinical Research InstituteConcordia UniversityDouglas Mental Health University InstituteMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCircadian rhythmCircadian clockChronotypeBiologyGenome-wide association studyWakefulnessCLOCKNeuroscienceGeneticsGeneSingle-nucleotide polymorphismGenotype

Abstract

fetched live from OpenAlex

The functions of circadian clocks and oscillators depend on a small number of genes. This collection of circadian clock genes forms an autoregulatory feedback loop, and provides the mechanism that underlies the operation of circadian clocks and oscillators in the brain and body (1). The resulting endogenous clocks and oscillators go on to drive diverse rhythms in behavior and physiology. Therefore, it was with some foresight that Hu et al . [2016] surveyed “23andMe” clients on their daily sleep-wake preferences, and performed an extensive genome-wide association study (GWAS) on 89,283 individuals (2). Even with a relatively coarse self-reported measure of “morningness”, the authors were able to identify 15 loci that were associated with preferred wake times, and notably, many of these loci related back to known circadian clock genes. Taken together, this study provides important new evidence that single nucleotide polymorphisms (SNPs) located close to certain clock genes, are associated with meaningful changes in our innate circadian preferences to wake early or to sleep late.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.421
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.310
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2016
Admission routes2
Has abstractyes

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