A <scp>SNP</scp> test to identify Africanized honeybees via proportion of ‘African’ ancestry
Bibliographic record
Abstract
The honeybee, Apis mellifera, is the world's most important pollinator and is ubiquitous in most agricultural ecosystems. Four major evolutionary lineages and at least 24 subspecies are recognized. Commercial populations are mainly derived from subspecies originating in Europe (75-95%). The Africanized honeybee is a New World hybrid of A. m. scutellata from Africa and European subspecies, with the African component making up 50-90% of the genome. Africanized honeybees are considered undesirable for bee-keeping in most countries, due to their extreme defensiveness and poor honey production. The international trade in honeybees is restricted, due in part to bans on the importation of queens (and semen) from countries where Africanized honeybees are extant. Some desirable strains from the United States of America that have been bred for traits such as resistance to the mite Varroa destructor are unfortunately excluded from export to countries such as Australia due to the presence of Africanized honeybees in the USA. This study shows that a panel of 95 single nucleotide polymorphisms, chosen to differentiate between the African, Eastern European and Western European lineages, can detect Africanized honeybees with a high degree of confidence via ancestry assignment. Our panel therefore offers a valuable tool to mitigate the risks of spreading Africanized honeybees across the globe and may enable the resumption of queen and bee semen imports from 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".