<scp>DNA</scp> barcoding largely supports 250 years of classical taxonomy: identifications for <scp>C</scp>entral <scp>E</scp>uropean bees (<scp>H</scp>ymenoptera, <scp>A</scp>poidea <i>partim</i>)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study presents DNA barcode records for 4118 specimens representing 561 species of bees belonging to the six families of Apoidea (Andrenidae, Apidae, Colletidae, Halictidae, Megachilidae and Melittidae) found in Central Europe. These records provide fully compliant barcode sequences for 503 of the 571 bee species in the German fauna and partial sequences for 43 more. The barcode results are largely congruent with traditional taxonomy as only five closely allied pairs of species could not be discriminated by barcodes. As well, 90% of the species possessed sufficiently deep sequence divergence to be assigned to a different Barcode Index Number (BIN). In fact, 56 species (11%) were assigned to two or more BINs reflecting the high levels of intraspecific divergence among their component specimens. Fifty other species (9.7%) shared the same Barcode Index Number with one or more species, but most of these species belonged to a distinct barcode cluster within a particular BIN. The barcode data contributed to clarifying the status of nearly half the examined taxonomically problematic species of bees in the German fauna. Based on these results, the role of DNA barcoding as a tool for current and future taxonomic work is discussed.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it