How does stocking density affect enhancement success for hatchery-reared red king crab?
Bibliographic record
Abstract
Stock enhancement of red king crab (Paralithodes camtschaticus (Tilesius, 1815)) could increase the crab population near Kodiak, Alaska, which collapsed in the 1980s and has not recovered. We conducted a field experiment examining the effect of juvenile red king crab density on enhancement success. Hatchery-reared crabs were released in plots near Kodiak at three densities: 25, 50, and 75 m−2. Crab densities were monitored for 6 months after release. Predation risk was measured via tethering experiments and predator density via quadrat and transect surveys. Neither migration nor mortality changed with crab density, but mortality rates decreased over time. Crab density did not affect predator density or predation risk, although predation risk decreased with time. Excluding the high initial mortality rate of 67.5%, the predicted survival after 6 months was 34%, which is better than the survival observed in a wild population. This suggests that red king crab enhancement is not predation limited and can occur at high densities. Further, processes affecting juvenile red king crab may not be strongly density dependent, at least at the scales and habitats tested.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".