Morphological and genetic concordance of cutthroat trout (<i>Oncorhynchus clarkii</i>) diversification from western North America
Bibliographic record
Abstract
The cutthroat trout (Oncorhynchus clarkii (Richardson, 1836)) is one of the most widely distributed species of freshwater fish in western North America. Occupying a diverse range of habitats, they exhibit significant phenotypic variability that is often recognized by intraspecific taxonomy. Recent molecular phylogenies have described phylogenetic diversification across cutthroat trout populations, but no study has provided a range-wide morphological comparison of taxonomic divisions. In this study, we used linear- and geometric-based morphometrics to determine if phylogenetic and subspecies divisions correspond to morphological variation in cutthroat trout, using replicate populations from throughout the geographic range of the species. Our data indicate significant morphological divergence of intraspecific categories in some, but not all, cutthroat trout subspecies. We also compare morphological distance measures with distance measures of mtDNA sequence divergence. DNA sequence divergence was positively correlated with morphological distance measures, indicating that morphologically more similar subspecies have lower sequence divergence in comparison to morphologically distant subspecies. Given these results, integrating both approaches to describing intraspecific variation may be necessary for developing a comprehensive conservation plan in wide-ranging species.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".