Baleen wear reveals intraoral water flow patterns of mysticete filter feeding
Bibliographic record
Abstract
A survey of macroscopic and microscopic wear patterns in the baleen of eight whale species (Cetacea: Mysticeti) discloses structural, functional, and life history properties of this neomorphic keratinous tissue, including evidence of intraoral water flow patterns involved in filter feeding. All baleen demonstrates wear, particularly on its medial and ventral edges, as flat outer layers of cortical keratin erode to reveal horn tubes, also of keratin, which emerge as hair-like fringes. This study quantified five additional categories of specific wear: pitting of plates, scratching of plates, scuffing of fringes, shortening of fringes, and reorientation of fringes (including fringes directed between plates to the exterior of the mouth). Blue whale baleen showed the most pitting and sei whale baleen the most scratching; gray whale baleen had the most fringe wear. The location of worn baleen within the mouth suggests that direct contact with the tongue is not responsible for most wear, and that flowing water as well as abrasive prey or sediment carried by the flowing water likely causes pitting and scratching of plates as well as fringe fraying, scuffing, shortening, and reorientation. Baleen also has elevated vertical and horizontal ridges that are unrelated to wear; these are probably related to growth and may allow for age determination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".