An updated range-wide assessment of Neophocaena: Threats and priorities for research and conservation
Bibliographic record
Abstract
The genus Neophocaena includes two species, the Indo-Pacific finless porpoise ( N. phocaenoides ) and the Narrow-ridged finless porpoise ( N. asiaeorientalis ). The Indo-Pacific species is found in coastal waters from the Persian Gulf through south and southeast Asia to as far north as the Taiwan Strait. The Narrow-ridged finless porpoise ranges from the Taiwan Strait to the waters of northern China, Korea, and Japan. Within N. asiaeorientalis there are two subspecies, the Yangtze finless porpoise ( N. a. asiaeorientalis ), found in the Yangtze River and adjoining lakes in China, and the East Asian finless porpoise ( N. a. sunameri ), found in coastal marine waters of China (including Hong Kong and Taiwan), Korea, and Japan. In 2019, an international workshop was held on finless porpoise research and conservation. Participants shared that, in many regions, information on distribution, abundance and population structure is lacking or inadequate. A global assessment of research is critical to provide a basis for conservation planning. Anthropogenic activities (i.e., habitat degradation, pollution, etc.) are known threats, with fisheries bycatch the primary threat throughout the known distribution of finless porpoises. To conserve these cetaceans, research priorities include studies of abundance and distribution, habitat and ecology, fisheries-related mortality, increased public awareness, and bycatch mitigation. • The Indo-Pacific finless porpoise meets the IUCN Red List criteria for “Vulnerable”. • The narrow-ridged finless porpoise meets the IUCN Red List criteria for “Endangered”. • An updated, global assessment of research is critical to provide baseline for conservation planning. • Both species are at risk of human-caused mortality. • Research priorities outlined in this article are needed for the conservation of both 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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".