The first consolidation of morphological, molecular, and phylogeographic data for the finely differentiated genus <i>Diaphoreolis</i> (Nudibranchia: Trinchesiidae)
Bibliographic record
Abstract
We demonstrate the application of the multilevel organismal diversity approach using the example of the nudibranch trinchesiid genus Diaphoreolis. For the first time, fine-scale morphological, genetic, and phylogeographic data are presented for all known species of the genus Diaphoreolis. One of the significant results of the present study and analysis is that the species D. stipata (Alder and Hancock, 1843) comb. nov., originally described from the North Atlantic and reinstated here, is revealed to be a sister species to the new NW Pacific species Diaphoreolis zvezda sp. nov. described from the Kuril Islands. Hidden diversity within the traditional taxon D. “ viridis” is revealed both in the North Pacific and the North Atlantic. A new subspecies, D. viridis emeraldi subsp. nov., is established for the Canadian and USA NE Pacific forms, and both morphological and molecular data are presented for the separate NW Pacific species D. midori. The present study combines practical results from a particular taxonomic group (nudibranchs) with generally important considerations for the expanding practice of uniting fine-scale morphological and molecular data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".