Irrawaddy dolphin <i>Orcaella brevirostris</i> in the Cambodian Mekong River: an initial survey
Bibliographic record
Abstract
Irrawaddy dolphins Orcaella brevirostiris are found in coastal waters from the Bay of Bengal east to Palawan, Philippines and south to northern Australia. They also occur in three large tropical river systems in South-east Asia: the Mekong, Mahakam and Ayeyarwady. In March and May 1997 approximately 350 km of riverine habitat in parts of north-east Cambodia were surveyed, discussions took place with local people, and reported dry season dolphin habitat was mapped. Our objectives were to investigate the status, habitat and distribution of dolphins in north-east Cambodia and identify threats to the continued survival of dolphins in the Mekong River Basin. Nine groups of dolphins were observed in the Mekong River. A ‘best’ estimate of 40 animals were seen. Irrawaddy dolphins were generally confined to sections of the river with water levels >8–10 m during the dry season. It appears that the Mekong River dolphin population is rapidly declining. In 1997 there were probably no more than 100¨C150 dolphins left in north-east Cambodia (including southern Laos) and no more than 200 within the entire Mekong River Basin, although these numbers remain tentative. Anthropogenic mortality is high, albeit largely unintentional, and there is considerable risk that the dolphin population will become locally extinct in the Mekong River in the near future. The establishment of community-managed deep water Fish Conservation Zones with government support may represent the best opportunity for reducing dry season dolphin mortality from large-meshed gillnet entanglement. Efforts to establish protected areas for dolphins are currently underway.
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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 | 0.001 | 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) | 0.002 | 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".