Visual health assessment of North Atlantic right whales (<i>Eubalaena glacialis</i>) using photographs
Bibliographic record
Abstract
Although trends in reproduction, mortality, and entanglement events have been analyzed for the endangered North Atlantic right whale (Eubalaena glacialis) population, no method has been available to assess individual right whale health. Here, we describe a technique for assessing health based on evaluation of selected physical parameters from archived photographs of right whales. A scoring system was developed to assess body and skin condition, blowhole cyamids, and rake marks in over 200 000 photographs. Comparison of body condition scores of females during calving and noncalving years found that females were significantly thinner in calving years and in the year after calving compared with the year before calving, showing that changes in body condition known to occur during the reproductive cycle can be successfully evaluated from photographs. Comparison of scores for all parameters between living whales and whales with more than a 5-year gap in sighting history ("presumed dead") found that presumed dead whales received health assessment scores indicating compromised health with body condition emerging as a key visual indicator. This health assessment method provides a new tool to monitor health trends in right whales at individual and population levels and may provide a model for assessments of other well-photographed cetaceans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".