Biological Clocks: Nature, Organization and Interactions
Bibliographic record
Abstract
Probably few domains of medical research have experienced so much interest within such short time frame as the identification and functioning of biological clocks. While circadian clocks are the best-known, very recent research has shown that biological clocks are numerous, closely interacting and, very importantly, that some are conserved from primitive organisms. While the central coordinator is located in the suprachiasmatic nucleus and mainly sensitive to light/darkness, also multiple peripheral clocks exist, which are sensitive to food and local metabolism and involved in both metabolism and vascular physiology work. The whole system works in a remarkably coordinated manner, although peripheral clocks can also work independently from the central clock. It can be seen how hormonal profiles vary physiologically over a 24h period and how disturbances in these processes can deregulate the system and the metabolic homeostasis. Many genes have just been identified, which largely help to understand functioning of the system and how de-synchronization (due in particular to modern lifestyle) can easily perturb it. The fact that essentially all factors known to be causally involved in the cardiometabolic syndrome (insulin resistance, vascular dysfunction) are involved strongly supports the key role clocks and their dysfunction may play in the present worldwide burden of this path ology. In particular it is impressive to note that simply changes in clock synchronization can induce these disorders, without necessarily invoking overeating and/or sedentarity usually considered as culprits. doi:10.4021/jem44w
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".