Ecology of Pacific white-sided dolphins (Lagenorhynchus obliquidens) in the coastal waters of British Columbia, Canada
Bibliographic record
Abstract
The ecology of Pacific white-sided dolphins (Lagenorhynchus obliquidens) in the Broughton \nArchipelago, British Columbia (BC), Canada was explored through photo-identification, mark- \nrecapture, acoustics, and sociality studies. New population parameters were estimated from \nphoto-ID data for the first time in this species. Abundance was highly variable, ranging from \n546 (95% CI: 293-1,018) to 2,889 (95% CI: 1,424-5,863), after accounting for the proportion \n(0.57; 95% CI: 0.55 - 0.60) of marked dolphins. A “match uncertainty” analysis showed that \nless strict matching criteria caused negative bias in abundance estimates and an apparent \nimprovement in precision. Estimates of survival rate ranged from 0.907 (SE=0.03) to 0.989 \n(SE= 0.066). Robust design analyses revealed random temporary emigration movement at 0.14 \n(SE=0.318) annually and no movement seasonally. The study revealed new evidence for \nphilopatry and sociality: some individuals were resighted over 19-year periods, and associated \npairs more than a decade apart. Evidence was found for a high degree of sociality. The mean \nproportion of calves was estimated as 0.0597 (SE=0.0083, 95% CI: 0.045-0.079) per capita, \ntranslating to an average probability of pregnancy in adult females of 0.238 (95% CI: 0.180- \n0.316) and an average interbirth interval of 4.2 years. Approximately 3.9% of dolphins bore \ninjuries from killer whales, but only 0.5% showed evidence of interactions with fishing gear or \npropellers. Acoustic evidence for population structure was equivocal, but warrants additional, \ntargeted research. Population viability analysis predicted an average rate of annual decline of - \n0.122 (95% CI: -0.143 to -0.101), given a range of input values in a sensitivity test, over the \nnext 50 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".