Beluga Whale Body Condition: Evaluating environmental variables on beluga body condition indicators in the Tarium Niryutait MPA, Beaufort Sea.
Bibliographic record
Abstract
The development of indicators as tools for ecosystem monitoring is a key step in the management of Marine Protected Areas (MPAs). This study uses previously developed sex-specific body condition indices, blubber thickness and girth, to assess temporal changes in body condition from 2000 to 2015 in harvested Eastern Beaufort Sea (EBS) beluga whales (Delphinapterus leucas). Specifically, the goals were to (1) examine seasonal and inter-annual trends of beluga body condition indicators over the harvest season; (2) evaluate associations of body condition indicators across sexes; and (3) test annual means of each body condition index for correlations to regional scale environmental drivers, (i.e. the Pacific Decadal Oscillation (PDO) and sea-ice minimum (SIM) in the Beaufort Sea). Significant seasonal changes in male blubber thickness and female girth indices demonstrated the importance of short term seasonal drivers. Whilst inter-annual changes in girth and blubber thickness indices revealed longer-term changes, that were correlated between males and females. Only the male girth index had significant relationships with environmental drivers: a negative relationship with the PDO at a zero-year lag ,and a negative relationship with the SIM at a two-year lag. [more in manuscript]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".