Bibliographic record
Abstract
Podalonia hirsuta (Scopoli, 1763) Distribution in Iran: Alborz (de Beaumont 1957; Ebrahimi 1993, 2014), Ardabil (de Beaumont 1957), Charmahal-o Bakhtiari (Ebrahimi 2014), East Azerbaijan (Ghazi-Soltani et al. 2010a, b; Dollfuss 2013b; Ebrahimi 2014), Golestan (Dollfuss 2013b, 2015; Ebrahimi 2014), Guilan (Ghahari et al. 2008; Ebrahimi 2014), Hamadan (Ebrahimi 2014), Isfahan (Samin et al. 2015), Khorasan-e Razavi (Ebrahimi 2014), Kohgiluyeh-va Boyerahmad (Dollfuss 2013b, 2015), Lorestan (Ebrahimi 2014), Markazi (Hadi et al. 2014), Mazandaran (de Beaumont 1957; Ebrahimi 2014), Qazvin (Sakenin et al. 2011b), Sistan-o Baluchestan (Ebrahimi 2014), Tehran (Ebrahimi 1993, 2014), West Azerbaijan, Zanjan (Ebrahimi 2014); no specific locality (Esmaili & Rastegar 1974). General distribution: Afghanistan, Albania, Algeria, Armenia, Andorra, Austria, Belarus, Belgium, Bulgaria, China, Croatia, Cyprus, Czech Republic, Denmark, Egypt, Estonia, Finland, France, Germany, Great Britain, Greece, Hungary, India, Iran, Ireland, Italy, Jordan, Kazakhstan, Kyrgyzstan, Latvia, Lebanon, Libya, Lithuania, Luxembourg, Macedonia, Malta, Morocco, Mongolia, Netherlands, Norway, Pakistan, Palestine, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, South Africa, Spain, Sweden, Switzerland, Syria, Tajikistan, Tibet, Tunisia, Turkey, Turkmenistan, Ukraine, Uzbekistan. Remarks: Two subspecies, Podalonia hirsuta mervensis (Radoszkowski, 1887) (Sakenin et al. 2011b; Ebrahimi 1993, 2014; Hadi et al. 2014) and Podalonia hirsuta hirsuta (Ghahari et al. 2008) have been recorded from Iran.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".