Is Native Crayfish Conservation a Priority for United States and Canadian Fish and Wildlife Agencies?
Bibliographic record
Abstract
Abstract Crayfish are key organisms in freshwater ecosystems across the United States (USA) and Canada, yet are among their most highly imperiled taxonomic groups. In 1996, a committee of prominent USA crayfish biologists warned of a crayfish imperilment plight and neglect of the fauna by natural resources agencies. It is unclear whether crayfish conservation has been prioritized by those agencies in the intervening decades. Our objective was to evaluate the status of crayfish conservation and management in 50 USA and 13 Canadian fish and wildlife agencies through a telephone survey. Fifty-one percent of agencies employed biologists to conduct crayfish work, mostly in the southern USA, and focused on threats (e.g., invasive species) or species’ distributions and conservation status. Of the 32 agencies working on crayfish, 59% considered them a priority, but 53% acknowledged insufficient funding. The most commonly cited information needs were threats, species compositions (native and introduced), distributions, conservation status assessments, and ecology. We report an encouraging but limited increase in agencies working on crayfish over the past two decades.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".