Phylogeny of Halictidae with an emphasis on endemic African Halictinae
Bibliographic record
Abstract
We review the literature on phylogeny, fossil record, biogeography, and social evolution in Halictidae. We then present a phylogenetic analysis of tribal, generic, and subgeneric relationships within the subfamily Halictinae using a combined data set of three nuclear genes: long-wavelength (LW) opsin, wingless , and EF-1α. The data set includes 89 species in 34 genera representing all four halictid subfamilies, and all tribes of the subfamily Halictinae. Our study provides several new insights into the phylogeny of the African Halictinae. First, our results support a close relationship between Mexalictus (a small genus of bees occurring at high elevations in the mountains of western North and Central America) and the African/Asian genus Patellapis . Second, our results support placement of the parasitic genus Parathrincostoma well within its host genus Thrinchostoma , suggesting that Parathrincostoma should be treated as a subgenus of Thrinchostoma. Finally, our data set provides strong support for the monophyly of Patellapis ( sensu Michener, 2000) and establishes monophyletic groups within the African subgenera that could be the basis for future taxonomic studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".