Data and code from: Sea ice perturbation and mass starvation of Thick-billed Murres
Bibliographic record
Abstract
During spring 2022, thousands of Thick-billed Murres (Uria lomvia) died on the southern Labrador and northeastern Newfoundland coasts. Location and timing of the event were compiled from public sources, including social media and institutions. Some retained carcasses were dissected and compared to healthy birds. The rapid-onset, five-week event lasted from March 18 to April 25, 2022, emanating from an impact site in southern Labrador. Extreme winds compacted and reduced sea ice area, which exposed sub-zero water temperatures and limited feeding options. Dissections were performed to determine body condition and demographics of birds affected. Neither sex nor age was associated with mortality, and a subset of carcasses tested negative for influenza A. Carcass masses averaged 65.5 % of the body mass of healthy birds, indicative of a threshold for stage III starvation (protein catabolism). Photographs and measurements showed significant pectoral muscle wasting, and pectoral mass was less than that of healthy birds. The probable cause of the die-off is starvation accelerated by a rapid drop in water temperature and limited foraging options driven by a sea-ice perturbation. Ocean-climatic variability and extreme events are expected to increase, posing challenges for polar seabirds.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.044 |
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".