Adaptive maintenance of European alleles in the Brazilian Africanized honeybee
Bibliographic record
Abstract
The Anthropocene is an epoch hallmarked by intensified human intrusion across ecosystems. One such intrusion is the movement and re-introduction of long-separated populations. By facilitating introgression - intraspecific genetic admixture - secondary contact can facilitate range expansion and the establishment of invasive species. The proximate mechanisms through which introgression facilitates expansion are rarely known (Bock et al., ; Rius & Darling, ), but managed species provide a useful avenue for exploration. Bee-keepers have been interbreeding highly diverged honeybee clades for centuries, often to introduce "useful" phenotypic variation to their stocks. Across the Western honeybee's (Apis mellifera) European range, this practice has not resulted in range expansion (Moritz, Härtel, & Neumann, ). In the Americas, however, introgression of European with African subspecies resulted in a widely publicized invasive population: The Africanized honeybee (AHB). In this issue of Molecular Ecology, Nelson, Wallberg, Simões, Lawson, and Webster () have made the first step towards understanding how this invasive species successfully spread across the Americas.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".