Prevalence and Abundance of Cyamid “Whale Lice” (<i>Cyamus ceti</i>) on Subsistence Harvested Bowhead Whales (<i>Balaena mysticetus</i>)
Bibliographic record
Abstract
We present findings on the prevalence and abundance of cyamid ectoparasites (Cyamus ceti) or “whale lice” on bowhead whales (Balaena mysticetus) harvested for subsistence in the Bering, Chukchi, and Beaufort Seas from 1973 to 2015. Cyamids were present on 20% of the 673 whales that were examined for cyamid ectoparasites. Logistic regression was used to determine factors associated with cyamid prevalence. The probability of cyamid presence increased with age, length, and improving body condition, but decreased over the past 35 years. Cyamid presence was also more probable on whales harvested in the spring than on those harvested in the fall. When present, cyamid abundance was typically low(< 10 per whale). Case histories provide ancillary information about the relationships between abundance of cyamids and their bowhead hosts. Environmental change and increasing anthropogenic disturbances are expected to occur in the Arctic regions inhabited by bowheads. We recommend continued monitoring of subsistence harvested whales for cyamids, as well as further investigations into the roles of environmental and anthropogenic variables in cyamid prevalence and abundance, as part of a comprehensive program of Arctic ecosystem assessment.
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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 | 0.001 |
| 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".