Spatial variability in rockfish (<i>Sebastes</i> spp.) recruitment events in the California Current System
Bibliographic record
Abstract
A general assumption regarding spatial patterns of recruitment variability is that species with similar early life history characteristics tend to covary in reproductive success over scales of 5001000 km. These assumptions are based on evaluation of recruitments from independent stocks, as few studies have assessed synchrony in recruitment within broadly dispersed stocks over finer spatial scales. We used data on age composition and landings to generate regional time series of recruitment deviations for three species of rockfish in the California Current System (Sebastes goodei, Sebastes entomelas, and Sebastes flavidus). We then used correlation analysis, principal components analysis, and other methods to evaluate the degree of synchrony among recruitment events in these regions. Results show that 51%72% of the year-to-year variability in recruitment is shared coastwide within these species, while a lesser but significant fraction of the variability is associated with finer scale geographic features.
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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 | 0.001 | 0.001 |
| 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".