Global systematic diversity, range distributions, conservation and taxonomic assessments of graylings (Teleostei: Salmonidae; Thymallus spp.)
Bibliographic record
Abstract
Abstract Graylings (Thymallus) are among the less well-studied groups of salmonid fishes, especially across their Asian distribution range. Here we perform a comprehensive global review of their phylogeography, systematic diversity and range distributions, including biogeographic reconstruction and assessment of both conservation and taxonomic status of each species. Based on a mitogenomic phylogenetic analysis, three approaches to the delineation of molecular operational units, and evaluation of 15 a-priori defined species, we provide biological support for the recognition of 13 grayling species, plus two additional species tentatively. Several instances of paraphyly and its potential effect on systematic inferences are discussed. Overall, the genus displays increasing species diversity and decreasing range size from higher to lower latitudes and ancestral trait reconstruction supports an East Asian origin for extant diversity, most likely centred in the Amur River drainage. Europe’s colonization byThymallustook place as early as the late Miocene, at least two colonisations of North America are supported, and multiple dispersal events likely took place into Western Siberia. The conservation status for the 15 taxa was estimated to be: 6 least concern, 1 near-threatened, 2 vulnerable, 3 endangered and 3 data deficient.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.000 | 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".