Ghosts of the coast: global extinction risk and conservation of sawfishes
Bibliographic record
Abstract
Abstract Sawfish are arguably the world's most imperilled marine fishes. All five species are classified as highly threatened with extinction: three are Critically Endangered (smalltooth sawfish Pristis pectinata , largetooth sawfish Pristis pristis, and green sawfish Pristis zijsron ); two are Endangered (narrow sawfish Anoxypristis cuspidata , and dwarf sawfish Pristis clavata ). Sawfishes are threatened primarily due to a combination of their low intrinsic rates of population increase, high catchability in fisheries, and high value. Sawfishes are among the world's largest marine fishes, and they are caught by a wide range of fishing gears owing to their tooth‐studded rostra being easily entangled. Sawfish fins are some of the most valuable for shark fin soup, and their rostra have long been traded as curios. In addition, they inhabit shallow coastal waters, estuaries, and rivers of the tropics and subtropics, down to a maximum depth rarely exceeding 100 m and are associated with threatened mangrove and seagrass habitats. Historically, sawfishes were distributed in the coastal waters of 90 countries and territories. Over the past century, their geographic distribution has been greatly diminished. For example, the smalltooth sawfish is now found in <20% of its former range. Globally, sawfishes are now entirely absent from 20 countries; 43 countries have lost at least one species. Sawfishes are legally protected, to some degree, in 16 of the 90 range states. These safeguards encompass, on average, 81% of their Extant distribution; however, the quality and breadth of protection varies dramatically across countries and species. Smalltooth sawfish currently has the least amount of such coverage of only half (49%) of Extant distribution. The global conservation strategy specifies actions to protect sawfish and their habitats. Such actions are urgently warranted to avoid global extinction and to restore robust populations for the benefit of coastal ecosystem function and biodiversity. © 2014 The Authors. Aquatic Conservation: Marine and Freshwater Ecosystems published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".