The first assessment of social organisation of the Indian Ocean humpback dolphin (<i>Sousa plumbea</i>) along the south coast of South Africa
Bibliographic record
Abstract
The Indian Ocean humpback dolphin (Sousa plumbea (G. Cuvier, 1829)) is the most endangered marine mammal species in South Africa, and the overall decline of its abundance and group size may affect the social organisation of the species, potentially accentuating its vulnerability. Understanding the social organisation is therefore particularly relevant to conservation efforts. From photo-identification surveys along the south coast of South Africa from March 2014 to June 2015, we quantified association patterns and investigated the social organisation of Indian Ocean humpback dolphins using the half-weight index, social cluster, and network analyses. During the 101 surveys conducted and 553 h of survey effort, 98 sightings of dolphins were recorded and 65 individuals identified. Using individuals seen at least three times, this study reveals that the social network is well differentiated, as strong social divisions exist between individuals that seem to be split into four distinctive social clusters. Network strength was low; approximately half of the associations were low to moderate, whereas some individuals were strongly associated, especially between four pairs of individuals. Although this study is based on a limited number of individuals, our study nevertheless suggests that the atypical strong social bonds recorded here could result from behavioural responses following the decline in group size and abundance.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".