Biomass indices of NAFO Division 4TVn fall spawning Atlantic Herring (Clupea harengus) from hydroacoustic surveys on spawning grounds
Bibliographic record
Abstract
Atlantic Herring in the southern Gulf of St. Lawrence (sGSL) are found in the area extending from the north shore of the Gaspé Peninsula to the northern tip of Cape Breton Island, including the Magdalen Islands. Fall spawning Herring in the sGSL are assessed using regionally disaggregated assessment models (North, Middle, South regions). Since 2015, hydroacoustic surveys were conducted annually on six major Herring fall spawning grounds in the sGSL. To account for missing samples, a predictive model of nightly Herring biomass was used to obtain a complete data grid and derive unbiased biomass indices. The covariates included in the negative-binomial model allowed to predict data for missing values in the observed data set. The trends in Herring biomass generated from this hydroacoustic survey closely match the trends observed in other population indices and stock status estimates from the population model. The North region biomass showed a decline to very low values in 2021. However, the Middle region decline in biomass seemed to be slower and with more interannual variation. Finally, a declining trend in the South region seemed to have reversed and biomass levels in 2021 were as high as in the beginning of the time series. The quality of the sampling and potential biases are discussed.
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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 | 0.001 |
| 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".