Body condition index in beluga whale (<scp><i>Delphinapterus leucas</i></scp>) carcasses derived from morphometric measurements
Bibliographic record
Abstract
Abstract Conservation efforts of the beluga whale (Delphinapterus leucas) of the St. Lawrence estuary include a mortality surveillance program which has the objective of documenting the causes of mortality. The evaluation of the animal's body condition is a key component in the diagnostic process. There is currently no consensual method to measure or calculate body condition indices in beluga whales. Morphological measurements recorded during necropsy were used to design a scaled mass body condition index that was compared to currently used visual evaluation, and to alternative morphological indices. Beluga whales were separated into two size‐based groups. The scaled mass index was well correlated with analog‐visual‐scale derived scores in beluga whale >290 cm, but not in animals <290 cm. Both methods showed almost perfect agreement regarding the categorization of carcasses belonging to the first quartiles. The alternative indices that were best correlated with the scaled mass index were those calculated using the sacral circumference and the ventral adipose thickness in animals <290 cm and the epaxial muscle mass and maximum circumference in beluga whales >290 cm. These scaled indices could provide objective tools to evaluate body condition of stranded beluga whales.
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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) | 0.001 | 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".