Bibliographic record
Abstract
Starvation periods are common for many animals, including fish, birds, and mammals. Many fish species exhibit extraordinary resilience to prolonged starvation, but the reasons for that and the mechanisms employed during these periods are poorly understood. This study shows that similar to mammals and birds, many fish species undergo three phases during starvation: (I) a short transient phase, (II) a long, protein conservation steady state phase with mainly fat oxidation as the primary energy source, and (III) a shift to protein mobilization as a main energy source. These starvation states and their transitions were quantified by a meta-analysis of large empirical data available in the literature, revealing that low critical levels of fat reserves trigger the transition to the third state. The critical fat level, denoted as γ (percentage of total lipid in body mass), ranges between 0.7% and 5%, depending on the species. It appears that these transitions in the energy mobilization phases are regulated by hormonal changes, including growth hormone (GH), leptin, cortisol, and ghrelin, but the exact mechanisms are still unclear and should be further investigated. Simulations in silico of starvation periods at various temperatures using a dynamic model indicated that temperature affects the length of Phase II because of changes in protein metabolism, with consequences on the ability to withstand prolonged starvation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".