A life cycle model to assess the abundance of black scabbardfish, a widely distributed fish with cryptic migrations
Bibliographic record
Abstract
The spatio-temporal dynamics of the black scabbardfish ( Aphanopus carbo Lowe, 1839) abundance in the northeast Atlantic was modeled using two linked Bayesian state-space models fitted to fishery-dependent data from trawlers operating to the west and north off the British Isles and longliners off the west coast of Portugal. The stage-structured life cycle models included species vital processes and fishing, and are linked by the migration flow between the two areas. Although data on spawner abundance and recruitment are missing, the hierarchical nature of state-space models allows a convenient representation of black scabbardfish dynamics using reliable data from the two studied areas, which correspond to two of the three main fishing grounds for the species. The approach presented is comparable to the few models developed for other species, such as European eel, where spawning and recruitment occur at restricted and distant regions. This approach is likely to remain the only option for black scabbardfish stock assessment and fisheries monitoring, as it is unlikely that data about the unobserved spawning and early life stages will become available in the near future.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".