A Theoretical Analysis of Diving Performance in the Weddell Seal (<i>Leptonychotes weddelli</i>)
Bibliographic record
Abstract
Marine mammals are constrained in their foraging behaviour because, as obligate air breathers, they must undertake regular trips to the water surface to satisfy the need for respiratory gas exchange. Maximum underwater endurance time is determined by O2 supply and demand, but this does not necessarily imply that O2 is the main factor regulating individual dive and surface times. This study presents a theoretical analysis of diving performance that emphasizes a key role for CO2 in the proximate control of diving behaviour. Computer simulations, based on a mathematical model of the mammalian cardiorespiratory control system, are used to investigate the influence of swimming to depth and other energetic stresses (feeding, thermogenesis, sleep) on predicted diving behaviour in an average adult Weddell seal. The plausibility of the proposed model is supported by the study, which replicated published observations of natural diving behaviour in this species. It is suggested that diving behaviour is tuned to oscillations in respiratory drive and that behavioural and physiological factors can alter the dynamic characteristics of the system to achieve a highly adaptable reciprocal interaction that blurs the boundary between physiology and behaviour.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".