Separating Historical Catches Among Pygmy Blue Whale Populations Using Recent Song Detections
Bibliographic record
Abstract
ABSTRACT In the Southern Hemisphere and northern Indian Ocean, there are at least five populations of pygmy blue whales, Balaenoptera musculus brevicauda , residing in the Northwest Indian Ocean (NWIO, Oman), central Indian Ocean (CIO, Sri Lanka), Southwest Indian Ocean (SWIO, Madagascar to Subantarctic), Southeast Indian Ocean (SEIO, Australia to Indonesia), and Southwest Pacific Ocean (SWPO, New Zealand). Each population produces a distinctive repeated song, but none have population assessments or reliable measures of historical whaling pressure. Here we created pygmy blue whale catch time series by removing Antarctic blue whale catches using length data and then fitting generalized additive models (based on latitude, longitude, and month) to contemporary song data (largely from 1995 to 2023) to allocate historical catches to the five populations. Most pygmy blue whale catches (97% of 12,207) were taken by Japanese and Soviet operations during 1959/1960 to 1971/1972, with the highest totals taken from the SWIO (6514), SEIO (2593), and CIO (2023), and lower catches from the NWIO (549) and SWPO (528). The resulting predicted annual catch assignments provide the first indication of the magnitude of whaling pressure on each population and are a key step toward assessing the status of these five pygmy blue whale populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 teacher head, 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".