Habitat partitioning and the influence of benthic topography and oceanography on the distribution of fin and minke whales in the Bay of Fundy, Canada
Why this work is in the frame
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Bibliographic record
Abstract
We collected data on the distribution of fin whales ( Balaenoptera physalus ) and minke whales ( Balaenoptera acutorostrata ) in the Bay of Fundy, Canada from a whale-watching vessel during commercial tours between July and September 2002. A single observer recorded the positions, species, numbers and surface activity of whales encountered during boat tours. We controlled for biased search effort by calculating sightings rates for both species in cells measuring 2′ latitude by 2′ longitude throughout the study area. Sightings rates were calculated by dividing the number of sightings of fin and minke whales in each cell by the number of visits by the tour boat to that cell. We used generalized additive models and generalized linear models to examine the influence of benthic topography on whale distribution patterns. Models showed a non-linear relationship for minke whale sighting rates with increasing benthic slopes and a linear relationship for minke and fin whale sightings rates with increasing water depth. Sightings of minkes were concentrated in areas subject to tidal wakes near the northern tips of Grand Manan and Campobello Island. Fin whales were also found off the northern tip of Grand Manan but sighting rates for this species were highest in areas with less benthic sloping topography adjacent to the relatively deep Owen Basin. Foraging was recorded during 87% of all whale encounters and our results indicate that whale distribution in this area is likely to be influenced by depth, bottom topography and fine scale oceanographic features that facilitate foraging.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it