Bibliographic record
Abstract
Circadian rhythms in mammalian behaviour and physiology rely on daily oscillations in the expression of canonical clock genes. Circadian rhythms in clock gene expression are observed in the master circadian clock, the suprachiasmatic nucleus but are also observed in many other brain regions that have diverse roles, including influences on motivational and emotional state, learning, hormone release and feeding. Increasingly, important links between circadian rhythms and metabolism are being uncovered. In particular, restricted feeding (RF) schedules which limit food availability to a single meal each day lead to the induction and entrainment of circadian rhythms in food-anticipatory activities in rodents. Food-anticipatory activities include increases in core body temperature, activity and hormone release in the hours leading up to the predictable mealtime. Crucially, RF schedules and the accompanying food-anticipatory activities are also associated with shifts in the daily oscillation of clock gene expression in diverse brain areas involved in feeding, energy balance, learning and memory, and motivation. Moreover, lesions of specific brain nuclei can affect the way rats will respond to RF, but have generally failed to eliminate all food-anticipatory activities. As a consequence, it is likely that a distributed neural system underlies the generation and regulation of food-anticipatory activities under RF. Thus, in the future, we would suggest that a more comprehensive approach should be taken, one that investigates the interactions between multiple circadian oscillators in the brain and body, and starts to report on potential neural systems rather than individual and discrete brain areas.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".