Pathologic Findings and Trends in Mortality in the Beluga ( <i>Delphinapterus leucas</i> ) Population of the St Lawrence Estuary, Quebec, Canada, From 1983 to 2012
Bibliographic record
Abstract
An isolated population of beluga (Delphinapterus leucas) inhabits the St Lawrence Estuary, Quebec, Canada. This population has failed to recover despite the prohibition of hunting >30 years ago, suggesting the presence of other limiting factors. The authors summarize the reported causes of death and propose risk factors to explain the lack of recovery of this population. From 1983 to 2012, a total of 472 beluga were found stranded. Complete necropsies were carried out on 222 beluga, including 178 adults, 25 juveniles, and 19 newborn calves. Infectious diseases, the most prevalent cause of mortality in this population, accounted for the death of one-third of all beluga (32%). Verminous pneumonia was the cause of mortality of 13 juvenile beluga (52% of juvenile beluga). A total of 39 malignant neoplasms, diagnosed in 35 beluga, caused the death of 31 beluga (20% of beluga >19 years old). Median age at diagnosis of cancer was 48 years (range, 30-61 years). Dystocia and postpartum complications were the cause of death in 18 beluga, accounting for 19% of the females >19 years old examined. The occurrence of parturition-associated complications, as well as mortality of calves <1 year old, have increased recently in this population and may be the probable cause of the recent decrease in the size of this population. One of the hypotheses proposed to explain the unusually high occurrence of some of the pathologic conditions observed in this population is chronic exposure to environmental contaminants.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".