The fly specimen that awaited a growing barcode community to be dusted off the shelves and given a name
Bibliographic record
Abstract
hile it can take an average of 21 years between the discovery and description of a new species1, the challenges of relating known taxa and the scarcity of high-quality specimens make the description of a new genus even more difficult and time-consuming. Our paper recently published in the Biodiversity Data Journal introduced a new fungus gnat genus-Coelosynapha-demonstrating that despite a taxon being shelved for a long time after discovery, strong collaborative networks spanning many countries combined with the power of DNA barcoding are greatly changing the pace at which we catalogue life. This story begins some 25 years ago when the late French entomologist Loc Matile (1938Matile ( -2000) ) sent Geir E.E. Sli (at the Natural History Museum in Oslo, Norway) illustrations and a brief one-page description of a potential new fly genus, belonging to fungus gnats of the family Mycetophilidae, based on a single specimen collected in Finland. Matile posed a seeming simple question to Sli, "Had this for yearsWhat do you think?" Unable to do much with the scarce material, the specimen was shelved, twice, for even after more specimens were found in Finland in 2009 and sent to a specialist in the USA, no progress was made.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".