Evidence of a Possible Decline since 1989 in False Killer Whales (<i>Pseudorca crassidens</i>) around the Main Hawaiian Islands
Bibliographic record
Abstract
Recent evidence indicates that there is a small, demographically isolated, island-associated population of false killer whales (Pseudorca crassidens) around the main Hawaiian Islands. Although it is known that false killer whales in Hawai‘i are sometimes killed or seriously injured in the Hawai‘i-based longline fishery, it is not known whether such interactions have resulted in a reduction in population size or whether other factors have been negatively influencing population size. We report the results of an aerial survey in June and July 1989, the purpose of which was to obtain a minimum count of the number of false killer whales around the main Hawaiian Islands. The false killer whale was the third most commonly seen species of odontocete off the island of Hawai‘i during the survey, representing 17% of sightings. Groups of more than 300 individuals were seen on three different days, with minimum counts of 380, 460, and 470 individuals in these groups. The encounter rate, relative species ranking, and average group size from the 1989 survey were all substantially greater than those from more recent aerial and ship-based surveys. The largest group observed in 1989 (470) contained almost four times as many whales as estimated for the entire main Hawaiian Islands from recent aerial surveys (121 individuals, CV = 0.47) or mark-recapture analyses (123 individuals, CV = 0.72). Therefore, the population of false killer whales around the main Hawaiian Islands may have declined substantially since 1989. The cause or causes of such a decline are uncertain.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".