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Record W1550149305 · doi:10.1002/9781118398814.ch15

Biological Timekeeping: Individual Variation, Performance, and Fitness

2014· other· en· W1550149305 on OpenAlex
Scott A. MacDougall‐Shackleton, Heather E. Watts, Thomas P. Hahn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntegrative Organismal Biology · 2014
Typeother
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsWestern University
Fundersnot available
KeywordsChronobiologyCircadian rhythmRhythmBiologyBacterial circadian rhythmsBiological clockDiversification (marketing strategy)Variation (astronomy)EcologyEvolutionary biologyPopulationSeasonalityOrganismNeuroscienceCircadian clockMedicineInternal medicine

Abstract

fetched live from OpenAlex

Virtually all parts of our planet exhibit cyclic changes in environmental conditions, and these cycles have persisted throughout the evolution and diversification of life. In response, most biological processes exhibit rhythms, and these rhythms can be observed at molecular, cellular, whole-organism, and population scales. As well, these rhythms exist at multiple time scales, including short-term oscillations, tidal, daily, lunar, and annual cycles. Biological rhythms have been extensively studied for many decades at a range of levels, including examination of the molecular basis of circadian clocks, neural and endocrine control of circadian cycles, seasonality and annual rhythms. This chapter briefly introduces fundamental concepts of the integrative physiology of circadian rhythms and seasonality with an emphasis on examples where individual variation in biological timekeeping relates to variation in performance or fitness.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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