Modeling the drift of European (<i>Anguilla anguilla</i>) and American (<i>Anguilla rostrata</i>) eel larvae during the year of spawning
Bibliographic record
Abstract
The distribution of the leptocephalus larvae of European (Anguilla anguilla) and American (Anguilla rostrata) eels collected during recent Sargasso Sea surveys was used to model larval drift. The drift trajectories of individual larva were back-calculated to the estimated time of spawning, using current data from two global oceanographic assimilation models. The results of both models give the same overall result; widespread spawning extended in time from December to March. The drift was also calculated forwards for approximately 1 year. The forward drift modelling showed that most leptocephali remained in the area south of the Subtropical Frontal Zone. One conclusion is that the majority of leptocephali remain trapped and possibly die in the retention area. A small proportion of leptocephali are entrained into the Gulf Stream system. An implication is that the spawning success may be highly sensitive to oceanographic and climatic factors that alter the dispersion of leptocephali out from the retention area. An alternative interpretation is that the surveys were made too late after the peak spawning period and that the core spawning area was missed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".