Bibliographic record
Abstract
The molecular mechanism of circadian rhythmicity is usually modeled by a transcription/translation feedback oscillator in which clock proteins negatively feed back on their own transcription to produce rhythmic levels of clock protein mRNAs, which in turn cause the production of rhythmic levels of clock proteins. This mechanism has been applied to all model organisms for which molecular data are available. This review summarizes the increasing number of anomalous observations that do not fit the standard molecular mechanism for the model organisms Acetabularia, Synechococcus, Drosophila, Neurospora, and mouse. The anomalies fall into 2 classes: observations of rhythmicity in the organism when transcription of clock genes is held constant, and rhythmicity in the organism when clock gene function is missing in knockout mutants. It is concluded that the weight of anomalies is now so large that the standard transcription/translation mechanism is no longer an adequate model for circadian oscillators. Rhythmic transcription may have other functions in the circadian system, such as participating in input and output pathways and providing robustness to the oscillations. It may be most useful to think in terms of a circadian system that uses a noncircadian oscillator consisting of metabolic feedback loops, which acquires its circadian properties from additional regulatory molecules such as the products of canonical clock genes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".