Differential effects of origin and salinity rearing conditions on growth of glass eels of the American eel <i>Anguilla rostrata</i>: implications for stocking programmes
Bibliographic record
Abstract
In this study, growth patterns were monitored in controlled fresh and brackish water (BW) conditions for 7 months during Anguilla rostrata glass eel and elver stages. Null hypotheses tested were that there is no significant difference in growth between glass eels (1) collected from two geographic regions typified by different sex ratios, (2) reared in fresh and BW and (3) due to origin x salinity interactions. It was found that young A. rostrata from Mira River (MR, Cape Breton, Nova Scotia, Canada, an area where both males and females occur) grew faster than those from Grande-Rivière-Blanche (Québec, Canada, an area where population are highly skewed towards females; 99-100%). Anguilla rostrata from both origins also grew faster in BW, although there was a trend for origin x salinity interactions whereby this effect was more pronounced for fish from the MR. The results support the hypothesis that salinity can influence growth patterns, as possibly can quantitative genetic differences between A. rostrata glass eels from different origins. Possible explanations for these patterns and potential consequences for sex determination and translocation programmes 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".