Regional variation in otolith Sr:Ca ratios of African longfinned eel <i>Anguilla mossambica</i> and mottled eel <i>Anguilla marmorata</i>: a challenge to the classic tool for reconstructing migratory histories of fishes
Bibliographic record
Abstract
Otolith Sr:Ca ratios of the African longfinned eel Anguilla mossambica and giant mottled eel Anguilla marmorata from nine freshwater sites in four rivers of South Africa were analysed to reconstruct their migratory life histories between freshwater and saltwater habitats. For A. mossambica, the Sr:Ca ratios in the otolith edge differed significantly among rivers and had large effect sizes, but did not differ among sites within a river. Otolith Sr:Ca ratios did not differ among rivers for A. marmorata. When rivers were pooled, the edge Sr:Ca ratios of A. mossambica were not significantly different from those of A. marmorata. According to the river-specific critical Sr:Ca ratio distinguishing freshwater from saltwater residence, most A. mossambica and A. marmorata had saltwater habitat experience after settlement in fresh water. This was primarily during their elver stage or early in the yellow eel stage. During the middle and late yellow eel stage, freshwater residency was preferred and only sporadic visits were made to saltwater habitats. The data also suggest that regional variations in otolith Sr:Ca ratios affect the critical Sr:Ca value and are a challenge for the reconstruction of migratory life histories that should be explicitly considered to avoid bias and uncertainty.
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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 | 0.000 |
| 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".