Age-structured meta-analysis of U.S. West Coast rockfish (Scorpaenidae) populations and hierarchical modeling of trawl survey catchabilities
Bibliographic record
Abstract
The swept-area estimates of biomass from the triennial groundfish trawl surveys on the shelf of the U.S. West Coast are believed to seriously underestimate rockfish (Scorpaenidae) stock biomasses. The bulk catchability (Q), defined to be the ratio between swept-area biomass and actual biomass, is herein modeled using a Bayesian age-structured meta-analysis of suitable West Coast rockfish stocks. Six shelf stocks of rockfish were used. The posterior distribution of Q was insensitive to choice of prior and gives a probability of about 0.05 that the bulk catchability of a randomly selected shelf rockfish species will be unity or higher. Between survey variability in bulk catchabilities was modeled as a multiplicative main effect. With individual posterior probabilities in excess of 0.99, bulk catchabilities were lower than normal in 1977 and 1980 and higher than normal in 1989 and 1998. The low catchabilities in 1977 and 1980 are consistent with previously identified problems with lack of bottom contact in the earlier years of the survey. Future work will extend the model to incorporate dynamic modeling of unassessed rockfish stocks, and suggestions for this are given.
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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 | 0.021 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".