Patterns in Recruitment of Marine Fishes in the Northeast Pacific Ocean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AbstractQuantitative and qualitative indices of year-class strength for 59 stocks of northeast Pacific fishes, representing 28 species and five geographic regions, were compiled to provide a comparison of recruitment patterns. Low-frequency and high-frequency patterns of recruitment were considered separately. Relationships between recruitment patterns of individual stocks were examined for correlation in year-class strength. Comparisons also were made between stocks representing different region/species categories (California stocks, northeast Pacific groundfish, Gulf and Canadian herring, and Bering Sea stocks). In addition, the high-frequency recruitment data set was analyzed for synchrony in the occurrence of extreme year classes. This study revealed four major features in patterns of recruitment of marine fishes along the west coast of North America. First, there is widespread synchrony of extreme year classes across the entire region studied. Second, the significant pairwise correlations were usuall...
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 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 it