Twenty years of Dipterology through the pages of Zootaxa
Bibliographic record
Abstract
We present a summary and analysis of the Diptera-related information published in Zootaxa from 2001 to 2020, with a focus on taxonomic papers. Altogether, 2,527 papers on Diptera were published, including 2,032 taxonomic papers and 1,931 papers containing new nomenclatural acts, equivalent to 22% of all publications with new nomenclatural acts for Diptera. The new nomenclatural acts include 7,431 new species, 277 new genera, 2,003 new synonymies, and 1,617 new combinations. A breakdown by family of new taxa and new replacement names proposed in the journal during the last two decades is provided, together with a comparison of Zootaxa's output to that of all other taxonomic publications on Diptera. Our results show that the journal has contributed to 20% of all biodiversity discovery in this megadiverse insect order over the last 20 years, and to about 31% in the last decade.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.036 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.013 |
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".