Evaluation of management performance of a new state-space model for pink salmon (<i>Oncorhynchus gorbuscha</i>) stock–recruitment analysis
Bibliographic record
Abstract
A new state space stock –recruitment (SR) model (XSR) was developed to treat observation errors in spawner and catch data, and nonstationarity in productivity for pink salmon ( Oncorhynchus gorbuscha) . Closed loop simulation was used to evaluate the management performance of XSR and compare its performance with that of a traditional SR model (TSR) and a Kalman Filter (KF). XSR produced higher expected catch than TSR and KF over a wide range of conditions. In some situations, TSR was preferred for reducing conservation concerns. However, large “outcome uncertainty” (OU) or implementation error in achieving desired management objectives can substantially reduce the management benefits of all assessment methods. Thus, OU should be considered in all management strategy evaluations, otherwise results will be misleading. Accordingly, reducing OU may better help achieve objectives.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".