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Record W3214850011 · doi:10.1111/jzs.12521

Chironomidae (Diptera: Insecta) of Qeshlagh River, Kurdistan: DNA and morphology reveal new genus, species, and faunistic records for Iran

2021· article· en· W3214850011 on OpenAlexaff
Habibollah Mohammadi, Hamed Ghobari, Edris Ghaderi, Foad Fatehi, Hemn Salehi, Armin Namayandeh

Bibliographic record

VenueJournal of Zoological Systematics & Evolutionary Research · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHymenoptera taxonomy and phylogeny
Canadian institutionsTrent University
FundersUniversity of Kurdistan
KeywordsChironomidaeBiologySister groupEcologyFaunaTaxonomy (biology)BiogeographyZoologyLarvaPhylogeneticsClade

Abstract

fetched live from OpenAlex

We assessed the Chironomidae fauna of Qeshlagh River, the second largest running water in the Kurdistan Province of Iran, and a major tributary of Sirwan River, using molecular and morphological methods. We identified a total of 35 Chironomidae species from the Qeshlagh River. Of these, Eraniella kurdistanensis gen. n., sp. n. (Orthocladiinae), Cricotopus (Cricotopus) hedayati sp. n., and Tanytarsus ronaki sp. n. are new to science. We combined DNA barcodes of cytochrome c oxidase subunit I gene obtained from the three new species with available sequences in GenBank and BOLD. The maximum likelihood (ML) tree placed Eraniella as a likely sister group of Parakiefferiella group of genera. The ML tree placed C. hedayati in Cricotopus festivellus group and a sister group of Cricotopus albiforceps (Kieffer, 1916). The ML tree placed T. ronaki as a sister group of Tanytarsus tamagotoi Sasa, 1983. This study also identified 11 new faunistic records for Iran and range extensions for the Palearctic. The importance of these local faunistic studies reflects broadly on the whole country, as the baseline information on the taxonomy and biogeography of the Iranian Chironomidae is scarce.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.110
GPT teacher head0.295
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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