Population estimation of bocaccio (Sebastes paucispinis) based on larval production
Bibliographic record
Abstract
We estimate the stock size of bocaccio ( Sebastes paucispinis ) in the Southern California Bight based on the production of larvae. Area-weighted total length compositions of preflexion larvae in 2002 and 2003 were determined from ichthyoplankton survey data. Larval length-to-age transition matrices were estimated from data derived from the enumeration of daily otolith increments. In combination, these results were used to estimate daily rates of larval production and mortality during surveys conducted in those years. Daily rates of larval production were expanded to annual production rates using information developed from the long-term seasonal distribution of larvae in CalCOFI surveys. Total annual larval production was translated to total spawning biomass by calculation of the female population weight-specific fecundity derived from a length-based life table analysis of adult reproductive parameters. Our results indicate that there were 6953 – 10 656 metric tons of bocaccio biomass (males and females >16 cm fork length) in the Southern California Bight during the survey years, which agrees with biomass estimates from a traditional stock assessment. Unique and problematic aspects of the reproductive biology of Sebastes are discussed, including multiple spawning, weight-specific fecundity that depends on size, and bias in fecundity data gathered from vitellogenic ovaries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".