Unveiling the unknown: an updated checklist, new species, new records, and molecular insights into Peru’s Psychodinae (Diptera: Psychodidae) diversity
Bibliographic record
Abstract
Abstract This article presents a comprehensive checklist of Peruvian Psychodines compiled from literature and examined specimens. We document a total of 45 species, along with 5 unidentified species, totaling 50 species records for Peru. We report the first records for Peru of Alepia bisubulata Duckhouse, 1968; Alepia diocula Quate & Brown, 2004; Atrichobrunettia (Pachybrunettia) triangularis Bravo, 2007; Atrichobrunettia (Polibrunettia) angelae Bravo, 2006; Atrichobrunettia (Polibrunettia) longipenis Bravo, 2006; Lepidiella pickeringi Quate, 1996; Platyplastinx culmosus Quate & Brown, 2004; and Psychoda divaricata Duckhouse, 1968. Moreover, we describe 8 new species: Australopericoma decima sp. nov.; Australopericoma sillua sp. nov.; Australopericoma sinuosa sp. nov.; Feuerborniella dentata sp. nov.; Maruina (Maruina) warmi sp. nov.; Philosepedon peruensis sp. nov.; Psychoda coniuncta sp. nov.; and Psychoda (Falsologima) paraxena sp. nov. Furthermore, we redescribe the male of A. diocula, matching males and females through DNA barcoding, and describing the female for the first time. In addition, we provide the cytochrome c oxidase I (COI) DNA barcodes for the newly described and newly recorded species. Our study compares different molecular delimitation analyses using various delimitation methods such as Assemble Species by Automatic Partitioning, Barcode Index Number assignments, Bayesian Poisson Tree Process model, and Species Identifier that resulted in different numbers of molecular operational taxonomic units, emphasizing the importance of integrative approaches in the documentation of Psychodidae diversity in Peru.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".