Estimation of Stock Reproductive Potential: History and Challenges for Canadian Atlantic Gadoid Stock Assessments
Bibliographic record
Abstract
The knowledge and scientific history of maternal and paternal aspects of reproduction dates back several decades, though only recently are fishery scientists and managers giving this subject area greater attention in the provision of management advice. This paper outlines and summarizes several recent advances made in understanding the importance of variation in gadoid reproductive output as a function of spawner age, size, maturation, condition and reproductive history. An assembled score-card applied to 45 Canadian Atlantic gadoid stock assessments conducted from 1985 to 1998 portrays the evolution and current degree to which this scientific knowledge has been incorporated into fishery advice in eastern Canada. For future research, recommendations are made which promote the integration of basic reproductive biology into groundfish stock assessments. These emerging policies encourage managers worldwide to initiate relevant sampling programs which will lead to improved stock conservation reference points. A new term referred to as stock reproductive potential (SRP) is introduced. Compared to spawning stock biomass and population fecundity, SRP more accurately represents the annual variation in a stock's ability to produce viable eggs and larvae that may eventually recruit to the adult population or fishery. SRP is a term (concept) which will likely evolve in such a manner as to provide a more accurate measure of a stock's reproductive potential.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".