Geographical distribution of the giant honey bee Apis laboriosa Smith, 1871 (Hymenoptera, Apidae)
Bibliographic record
Abstract
Worldwide pollinator declines have dramatically increased our need to survey and monitor pollinator distributions and abundances. The giant honey bee, Apis laboriosa, is one of the important pollinators at higher altitudes of the Himalayas. This species has a restricted distribution along the Himalayas and neighbouring mountain ranges of Asia. Previous assessments of its distribution, published more than 20 years ago, were based on museum specimens. Since then, 244 additional localities have been revealed through field trips by the authors, publications, and websites. We present a revised distribution for A. laboriosa that better defines its range and extends it eastward to the mountains of northern Vietnam, southward along the Arakan Mountains to west-central Myanmar, into the Shillong Hills of Meghalaya, India, and northwestward in Uttarakhand, India. This species is generally found at elevations between 1000–3000 m a.s.l.. In northeastern India A. laboriosa colonies occur during summer at sites as low as 850 m a.s.l. and some lower elevation colonies maintain their nests throughout the winter. Finally, we report three regions in Arunachal Pradesh, India, and nine locations in northern Vietnam, where we observed workers of A. laboriosa and A. dorsata foraging sympatrically; their co-occurrence supports the species status of Apis laboriosa.
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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".