Transoceanic migration rates of young North Pacific albacore, Thunnus alalunga, from conventional tagging data
Bibliographic record
Abstract
This study summarizes US and Japanese historical North Pacific albacore ( Thunnus alalunga) tagging data and uses maximum likelihood methods to estimate seasonal migration rates of young North Pacific albacore. Previous studies related to North Pacific albacore migration have found that the frequency of albacore migrations is difficult to quantify because of inadequate amounts of tags released by the US tagging program in the western Pacific. Use of the combined Japan and US tagging data solves this problem. This study also incorporates specific seasonal migration routes, hypothesized in past qualitative analyses, to avoid overparameterization problems. The estimated migration patterns qualitatively correspond to those from previous studies and suggest the possibility of frequent westward movements and infrequent eastward movements in the North Pacific. This frequent westward movement of young albacore in the North Pacific would correspond to a part of albacore life history in which immature fish recruit into fisheries in the western and eastern Pacific and then gradually move near to their spawning grounds in the central and western Pacific before maturing.
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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".