An investigation of the biological basis of recruitment, growth and adult survival rate variability of Pacific herring (<i>Clupea pallasi</i>) from British Columbia: a synthesis
Bibliographic record
Abstract
Abstract I explored the biological basis of variation in recruitment (age 3 abundance), growth and age‐specific adult survival rate for the major populations [West Coast Vancouver Island (WCVI), Strait of Georgia, Central Coast, North Coast and Haida Gwaii] of Pacific herring (Clupea pallasi) that inhabit British Columbian waters. The analyses were based on a synthesis of time series of empirical observations of herring population characteristics (egg deposition, age‐specific abundance and size) and prey, competitor and predator biomass/abundance. Recruitment was not correlated among populations. Recruitment variability was explained for WCVI herring only, as a consequence of prey (the euphausiid Thysanoessa spinifera) biomass during August in each of the first 3 years of life, and the biomass of piscivorous Pacific hake (Merluccius productus) during the first year of life. Recruit mass and adult mass‐at‐age were correlated among populations and over ages within populations. Recruit mass was affected by T. spinifera biomass in August of the first and third years of life. Adult mass‐at‐age variability was determined mainly by size at the beginning of the growth season, but also by T. spinifera biomass in August. Age‐specific adult survival rates were not correlated among the five populations. Survival rates decreased with age; there were additional population‐specific effects of somatic mass and T. spinifera biomass in August. The analyses were repeated using physical oceanographic explanatory variables. Only recruit mass variation was explained significantly by physical oceanographic variables, and the biological‐based explanation of recruit mass variability accounted for more of the variation.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".