Ecological lifestyle and gill slit height across sharks
Bibliographic record
Abstract
Abstract Morphology that is linked to metabolic rate – metabolic morphology – provides broad comparative insights into the physiological performance and ecological function of species. However, some metabolic morphological traits, such as gill surface area, require costly and lethal sampling. Measurements from anatomically-accurate drawings, such as those in field guides, offer the opportunity to understand physiological and ecological relationships without the need for physical, lethal sampling. Here, we assess the relationship between the metabolic physiology and ecology of nearly all extant sharks. Specifically, we examine the relationship between gill slit height and each of the three traits that comprise ecological lifestyle: activity, maximum size, and depth. We find that gill slit heights are positively related to activity (measured by the aspect ratio of the caudal fin) and maximum size but negatively related to depth. We also show that gill slit height is best explained by the suite of ecological lifestyle traits rather than any single trait. These results suggest that more active, larger, and shallower species have higher metabolic demands and that these greater metabolic demands can be estimated from external morphological and ecological traits. Our work demonstrates that meaningful ecophysiological relationships can be revealed through measurable metabolic morphological traits from anatomically-accurate drawings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".