Demographic attributes of yellow-phase American eels (<i>Anguilla rostrata</i>) in the Hudson River estuary
Bibliographic record
Abstract
Management of American eels (Anguilla rostrata) requires an understanding of how demographic attributes vary within large estuaries. Yellow-phase American eel length and age structure, growth, dispersal, nematode infestation rates, loss rate (natural mortality and emigration), and production were measured at six sites throughout the tidal portion of the Hudson River. Short-term dispersal was low, with >70% of eels at all sites captured <1 km from their original tagging area. Length was similar among sites (total length = 45.7 ± 0.3 cm), whereas age was substantially lower for brackish-water sites (8 ± 4 years) than for freshwater sites (17 ± 4 years). Growth was higher for brackish-water sites than for freshwater sites (8.0 cm·year –1 and 3.4 cm·year –1 , respectively). From 1997 to 2000, infestation by the exotic nematode Anguillicola crassus increased dramatically in mean intensity as well as prevalence. Annual loss rates measured for the six sites varied between 9% and 24%, with no statistical difference between freshwater and brackish-water sites. Estimated eel production was higher in a brackish-water habitat (1.10–1.77 kg·ha –1 ·year –1 ) than in a freshwater location (0.21–0.58 kg·ha –1 ·year –1 ). The results of this study support a recent proposal to establish freshwater areas as exploitation reserves.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".