How can the feeding habits of the sand tiger shark influence the success of conservation programs?
Bibliographic record
Abstract
Abstract The feeding habits of the sand tiger shark Carcharias taurus, one of the most threatened sharks of the world, are poorly known. Sand tiger sharks are critically endangered in the South‐west Atlantic. Since 2007, the law requires that all individuals caught in recreational fisheries off Argentina must be released. Using data from a north Patagonian recreational fishery (n=164 stomachs with contents), we analyzed the diet of sand tiger sharks in relation with size, sex, maturity stage and season; assessed prey consumption patterns and hooking location; and estimated diet overlap with fishery landings. Sand tiger sharks consumed mainly teleosts (55.4% of the total prey number, N) and elasmobranchs (41.84%N), and ate more benthic elasmobranchs (batoids and angel sharks) as they become larger. Sharks swallowed prey mostly in one piece (93.7%) and were hooked mainly in internal organs (87.4%, n=175), causing occlusion and perforation of the esophagus and stomach, and lacerations to the pericardium, heart and liver. Sand tiger sharks fed on the most heavily landed species, overlapping almost completely (>90%) with fishery landings. Conservation plans should take into account that releasing hooked sharks could be insufficient to minimize fishing mortality and that competition for food with fisheries is likely to occur.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".