Past and present sawfish (Pristidae) records from India
Bibliographic record
Abstract
Overfishing, as well as habitat loss and degradation, has led to major population declines and local extinctions of sawfishes (Pristidae) globally. Four sawfish species reportedly occur in India; however, records have been limited to opportunistic commercial catch and landing reports. Here, we provide the first comprehensive review of published and grey literature on sawfish records from India, including opportunistic observations of sawfish rostra offerings to religious places, highlighting the cultural significance of these species locally. In total, 223 recorded capture events were compiled between 1794 and 2022, with largetooth sawfish Pristis pristis (n = 82), followed by narrow sawfish Anoxypristis cuspidata (n = 32), being the dominant species reported. In addition to marine fisheries, 8 reports of sawfish were reported from freshwater systems. The wide range of rostra sizes and total lengths recorded also suggests that India’s waters harbour various life history stages of sawfish. When caught, sawfish livers were utilised to produce oil, meat was locally consumed, and fins were exported. Despite being legally protected in India since 2001, 63 incidental captures were recorded from landings, suggesting various levels of awareness and enforcement of catch bans across the country. To avoid extinction of these species in India, we emphasise the need to conduct culturally associated awareness programs with coastal communities, encourage safe release and improve handling practices with fishers, identify critical habitats, and strengthen enforcement for mandatory live release.
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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 | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".