Cheilosia (Cheilosia) pseudogrossa Stackelberg 1968
Bibliographic record
Abstract
Cheilosia (Cheilosia) pseudogrossa Stackelberg, 1968 Fig. 58 Cheilosia pseudogrossa Stackelberg, 1968: 228. Cheilosia pseudogrossa – Stackelberg & Richter 1968: 248. — Stackelberg 1970: 59. — Barkalov 1993: 714. — Barkalov & Mutin 2018: 483. — Mengual et al. 2020: 20. Cheilosia pseudogrossa Stackelberg, 1956 [sic] — Gujabidze 2002: 246. Differential diagnosis Cheilosia pseudogrossa is genetically and morphologically very similar to C. grossa. It can however easily be identified from it by the pilose face (bare in C. grossa). Other differences in the male (we could not study the female) include the postpedicel being dark orange to brown (black in C. grossa), face ventrolateral of facial tubercle not swollen (swollen in C. grossa), pile on anepimeron with straight apex (with wavy apex in C. grossa) and terga III–IV pruinose (lateral sides of tergum III widely shiny and tergum IV entirely shiny except anterior margin in C. grossa). Material examined Not collected in 2018, but collected in 2023. GEORGIA – Mtskheta-Mtianeti • 1 ♂; Lutkhubi; 42.3984° N, 44.7996° E; 2068 m a.s.l.; 8 May 2023; S. Bot leg.; SBA, SB.003236 = ZFMK-TIS-8027992 • 1 ♂; Lutkhubi; 42.4006° N, 44.7956° E; 2130 m a.s.l.; 8 May 2023; F. Van de Meutter leg.; FMT, ZFMK-TIS-8027940. Genetics The two DNA sequences of C. pseudogrossa cluster together with high support (BS = 99.7%) in our NJ tree. See Genetics under C. grossa. Biology During our expeditions, collected on 8 May at an altitude between 2068 and 2130 m a.s.l. on flowering willow Salix sp. Distribution Caucasus (Abkhazia region, Georgia, Russia).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads agree on what is shown here.
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".