North Atlantic humpback whale (<i>Megaptera novaeangliae</i>) hotspots defined by bathymetric features off western Puerto Rico
Bibliographic record
Abstract
North Atlantic humpback whales (Megaptera novaeangliae (Borowski, 1781)) are increasing in number, necessitating current data from winter areas for assessing potential interactions with humans. Occurrence patterns of humpback whales wintering off Puerto Rico were investigated to predict where whales aggregate in nearshore areas. Here we describe the relationship between group associations of humpback whales and bathymetric features off western Puerto Rico. Data were collected from 2011 to 2014. Effort consisted of 240.9 vessel h, 13.0 aerial h, and 303.6 h of land observations conducted over 165 days. A total of 197 humpback whale groups were observed with n = 331 individuals: 91 (46.2%) singletons, 67 (34%) dyads, 17 (8.6%) mother–calf pairs, 8 (4.1%) competitive groups, 8 (4.1%) mother–calf–escort groups, and 6 (3.1%) mixed-species associations. A linear regression model supported that group composition correlated with hotspots associated with four bathymetric features. Dyads and competitive groups were dispersed among features in deeper water. Singletons were observed farther from a shelf edge, whereas singing males were closely associated with a shelf edge. Mother–calf pairs occurred nearshore in shallow water; however, when mother–calf pairs were sighted with an escort, they were offshore. This study is especially important ahead of possible removal from the Endangered Species list.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".