Oceanic water temperatures less than 20°C may largely adjust for underestimation of European elver otolith ages
Bibliographic record
Abstract
Abstract European eel Anguilla anguilla otolith‐based elver ages may be substantially adjusted higher by migratory path oceanic water temperatures. Water temperatures <20°C increased temperature‐adjusted otolith ages of Japanese glass eels and elvers. Migration periods to the northern Vilaine and Severn Rivers were estimated at 785 days (2.15 years) and 781 days (2.14 years), respectively, and 958 days (2.62 years) for the southern Rio Minho, assuming a mean spawning date of 9 February (66 days shorter with a mean spawning date of 16 April). For a 9 February mean spawning date, temperature‐corrected otolith ages were higher than otolith ages by 34.4–92.7%. Higher migration route water temperatures reduced the temperature‐adjustment of otolith ages. Another approach to the temperature‐correction of otolith ages underestimated by 5.6–28.1% the migration period (days) to the southern Rio Minho and overestimated by 12.4–13.4% that to the two northern rivers. The effect of recent higher North Atlantic water temperatures on otolith daily growth increments remains to be learned. The difference between temperature‐adjusted otolith and observed ages differed little between earlier and later mean spawning dates. Otolith ages for glass and elver European eels should not be used if unadjusted for migration route water temperatures and used cautiously after adjustment for low oceanic, estuarine, and perhaps freshwater temperatures; even then otolith ageing issues remain. A greater understanding of oceanic migratory paths and durations is needed for European eels.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".