<i>Notodonta valeria</i>, a new species (Lepidoptera, Notodontidae) from China, with taxonomic remarks on <i>Notodonta ziczac</i> (Linnaeus, 1758)
Bibliographic record
Abstract
A new species of Notodonta Ochsenheimer, 1810, N. valeria sp. n., from the Chinese Sichuan and Qinghai provinces is described. The new species differs in appearance, genitalia and DNA from its closest known relatives, Notodonta ziczac (Linnaeus) and Notodonta derbendica Daniel, 1965 stat. n. described from Europe and Iran, respectively. The genus Notodonta in the Palearctic is distributed in North Africa, Europe, Middle Asia, Russia (including Siberia), Japan, Korea and China. Three of the known 13 species are found in North America (Schintlmeister 2008). Sampling was conducted using UV lights and DNA barcodes (658 base pairs of Cytochrome Oxidase Subunit I 5' region, COI-5P) were prepared by Hebert's laboratory at the University of Guelph. Male and female genitalia dissections following Lafontaine (2004) were mounted in euparal, and a Wild M3Z microscope and Canon EOS 350D camera were used to prepare images. Taxonomic information and nomenclature follows Daniel 1965, Schintlmeister & Fang 2001, Schintlmeister 2008, Wu & Fang 2001. Acronyms used below: AFM = Alessandro Floriani (Milan, Italy); MNHU = Museum für Naturkunde der Humboldt Universität zu Berlin; MWM/ZSM = Museum Thomas Witt (Munich, Germany) /Zoologische Staatssammlung, Munich (Germany); NRCV = Nature Research Centre (Vilnius, Lithuania); OPB = Oleg Pekarsky (Budapest,Hungary); PMM = Pavel Morozov (Moscow, Russia).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".