Complementarity and discriminatory power of genotype and otolith shape in describing the fine-scale population structure of an exploited fish, the common sole of the Eastern English Channel
Bibliographic record
Abstract
Marine organisms show population structure at a relatively fine spatial scale, even in open habitats. The tools commonly used to assess subtle patterns of connectivity have diverse levels of resolution. We have assessed the discriminatory power of genetic markers and otolith shape to reveal the population structure of the common sole (Solea solea), living in the Eastern English Channel stock off France and the UK. The aims were to (i) inform the short and long-term population structure by comparing genetic and otolith shape approaches, and (ii) combine the tracers in a single analysis to assess the interest of a combined approach. First, we applied Single Nucleotide Polymorphisms to assess population structure at an evolutionary scale. Then, we tested for spatial segregation of the subpopulations using otolith shape as an integrative tracer of life history. Finally, we combined the genotypes and otolith phenotypes in a supervised machine learning framework to probabilistically assign adults to subpopulations. Genetic assignments and otolith shape analyses provided congruent results suggestive of a metapopulation structure for the common sole of the Eastern English Channel. Despite congruent results from genetics and otolith shape, the combined analysis did not provide realistic reallocation probabilities. Our findings support the idea that independent analyses of tracers provide fruitful insights and that a combined approach should be preferred when a large and balanced number of fish is available for each tracer analyzed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".