Rostrum abnormalities in the endangered Indian Ocean humpback dolphin (<i>Sousa plumbea</i>) in South Africa
Bibliographic record
Abstract
Morphological abnormalities in wild animals can be indicators of the underlying health of a population and may be determined through routine photographic surveys. Here, we assess unusual rostrum conditions in Indian Ocean humpback dolphins (Sousa plumbea) inhabiting South African coastal waters to understand the rate of prevalence of abnormal rostrums and formulate hypotheses on potential causes. Photographic data were collated from systematic boat surveys and opportunistic sightings, obtained between April 1998 and March 2021 in various regions along the South African coast. Overall, 31 unique individuals were found with abnormal rostrum conditions, varying from slight misalignments to severe wounds and/or aberrant morphologies. In most cases, injuries were likely caused by natural events during the animal's life history such as interactions with sharks and/or reef-associated hunting strategies. Mark-recapture data indicated that individuals had survived with these injuries for up to 10 years. This study reports the highest incidence of rostrum abnormalities in the species. As numbers reflect only those that have survived their injuries, they are considered a minimum estimate. A better understanding of the cause(s) of these injuries is important given the endangered status of this species.
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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 | 0.001 | 0.001 |
| 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".