Bibliographic record
Abstract
Chortoglyphus arcuatus (Troupeau, 1879) Distribution in Iran – West Azerbaijan Province: Region not mentioned, Mazandaran Province: Region not mentioned (Esmaili 1983; Faraji 1993b; Mirfakhraii 1994), Razavi Khorasan Province: Mashhad (Khaleghabadian et al. 2012), Guilan Province: Masal, Sowme'eh Sara, Rezvanshahr, Rice Research Institute of Iran, Anzali, Kuchesfahan, Fuman (Noei 2007; Noei and Ostovan 2012). General distribution – Barbados, Belgium, Canada, China, Croatia, Czech Republic, Egypt, England, France, Germany, Greece, Hong Kong, Ireland, Italy, Netherlands, New Zealand, Poland, Russia, Taiwan, Thailand, Wales (Hagstrum et al. 2013). Collection place(s) – Houses, rice barley, barley sweeping, bean curd, cereal, Chinese medicine, clover seed (red), dried fruit, dried vegetable, grain, grass seed, hay, herb, lentil, maize, malt, millet, mushroom, oat, poppy seed, potato flour, poultry mix, residue, rice, rice (husked), rye, shrimp (dried), soya sweeping, squid (dried), sugar beet seed, sweeping, sweetpotato chip (dried), wheat, wheat flour, wheat flour sweeping, stored rice, rice dust and debris (Esmaili 1983; Faraji 1993b; Mirfakhraii 1994; Modarres Awal 1994; Noei 2007; Noei and Ostovan 2012; Hagstrum et al. 2013).
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".