Using morphology to infer physiology: case studies on rorqual whales (Balaenopteridae)
Bibliographic record
Abstract
Whales are important model systems for understanding the physiological and ecological consequences of extreme body size. However, whales are also some of the most difficult animals to study because their large size precludes experimental studies under controlled conditions. Here we review a wide range of morphological studies that enable greater inference of physiological processes. In particular, we focus on baleen whales that exhibit extensive diving and foraging adaptations. Using morphological data, we (i) explore the biomechanics and sensory physiology of lunge-feeding rorqual whales (Balaenopteridae), (ii) determine the effects of scale and diving pressures on the circulatory physiology of fin whales (Balaenoptera physalus (L., 1758)), and (iii) better understand the adaptations of the cetacean respiratory system that facilitate a fully aquatic life history. These studies underscore the value of understanding functional morphology in animals that cannot be studied using traditional laboratory techniques.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".