Bibliographic record
Abstract
Subtribe Thiratoscirtina Bodner & Maddison, 2012 Remarks. The Thiratoscirtina is a major species-rich group in African tropical forests – e.g., more than 52 species were found in 17 days of field work in Gabon by the second author – and yet its genera received little attention before Wanda Wesołowska began studying them. Of those 52 Gabonese species, we are able to confidently place fewer than half into described genera. Uncertainty in the group’s generic limits is heightened by their unusually variable genitalia, by the lack of taxonomic synthesis between vouchers of molecular data (Bodner & Maddison 2012), and by the growing number of named taxa. Faced with this, we could decide to stop describing species until genera are settled, to describe a new genus for each species of unclear affinity, or to place new species tentatively into existing genera. Describing species is so important for conservation and comparative biology that we do not want to hold back descriptions. We have thus chosen to describe two species here tentatively in Ajaraneola and Nimbarus, even though we must admit that their generic placements may change.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".