Strains of <i>Apis mellifera ligustica</i> honey bees artificially bred for apicultural traits are not consistently differentiated by mitochondrial DNA genome markers
Bibliographic record
Abstract
Strains of the Italian honey bee Apis mellifera ligustica Spinola, 1806 are selectively bred for desirable apiculture traits. Ma et al. compared SNP differences in mtDNA genomes between a strain bred for enhanced royal jelly production (RJB) and an unselected strain (ITB). Kim et al. compared SNP and intergenic repeats differences between a Varroa mite resistant strain bred for high-hygienic behavior (HHB) and an unselected low-hygienic strain (LHB). Phylogenetic comparison of 23 complete A. m. ligustica mtDNA sequences, including the HHB and LHB strains and 14 RJB and ITB haplotypes, shows significant intrasubspecific clade structure for SNP differences and amino acid substitutions; however, this structure is not diagnostic of the strains under selection. RJB strains occur in three separate clades, and along with HHB are frequently identical or near-identical to other haplotypes. Differences between the selected and unselected strains appear to arise from coincidental fixation of alternative SNPs in different clades. Numbers of repeats show little or no phylogenetic signal: similarities are symplesiomorphic and differences convergent. Evaluation of the diagnostic and (or) adaptive significance of mtDNA markers requires broad knowledge of within-subspecies polymorphism.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".