Bibliographic record
Abstract
Cheilosia (Montanocheila chrysocoma (Meigen, 1822) Fig. 20 Syrphus chrysocomus Meigen, 1822: 280. Cheilosia chrysocoma – Gujabidze 2002: 246. — Mengual et al. 2020: 25. Differential diagnosis Cheilosia chrysocoma stands out amongst most other species of Cheilosia by usually having a furry, fox red body pile (Fig 20A, C). Within the subgenus Montanocheila the male can be identified by surstylus being ca five times as long as wide, with pointed tip (Fig. 20B, in the other species of Montanocheila occurring in the Caucasus, the surstylus is not longer than three times width). The female has the posterior margin of tergum V rounded (in the other species of Montanocheila occurring in the Caucasus the posterior margin of tergum V is more angulated). Material examined Species not collected. Genetics All DNA barcodes of C. chrysocoma from outside the Caucasus cluster together with a high support (BS = 99.1%). Remarks Gujabidze (2002) and Mengual et al. (2020) cite the records of this species from Mtskheta (Mtskheta-Mtianeti) included in an unpublished manuscript by Zaitsev; see references in Gujabidze (2002). The presence of this species in the Caucasus needs confirmation. Distribution Europe, European parts of Russia, and Siberia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".