An overview of the Iranian Chironomidae (Diptera) diversity with an updated checklist with the provincial distribution
Bibliographic record
Abstract
An assessment of the Iranian Chironomidae diversity with an updated checklist is provided. In total, 65 species from 12 out of 31 provinces of Iran are recorded. Based on the distributional data obtained for these species, much of the biodiversity of this country is unknown, especially for central, south, and eastern regions. The most studied area of the country is Kurdistan Province in the west, with 36 known species, of which three new species and 31 new faunistic records were recently obtained from studies of rivers and streams of this region. Based on the records obtained, we can tentatively report Boreoheptagyia iranica Makarchenko, 2020, Palatovia lorestanica Makarchenko et Semenchenko, 2020, and Eraniella kurdistanensis Namayandeh, Ghaderi, Ghobari et Mohammadi, 2021 described from the Zagros Mountains are endemic to the country. The biogeographical location of Iran and its diverse geography, habitats, and reservoir of freshwaters suggest that the diversity of Iranian Chironomidae is far more than the current estimate. Therefore, there is an urgency in obtaining baseline data on the distribution and taxonomic abundance to understand the Iranian Chironomidae’s diversity
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".