Southeast Asian Bumblebee Specimen Database
Bibliographic record
Abstract
List of Southeast Asian bumblebee specimens (the CT database), including CT ID, collection (BEEP=Bee Protection Laboratory, Department of Biology, Chiang Mai University, Chiang Mai, Thailand; CUNHM= Chulalongkorn University Natural History Museum, Bangkok, Thailand; ACMU= Department of Entomology and Plant Pathology, Chiang Mai University, Chiang Mai, Thailand; FRIM= Entomological Reference Collection, Forest Research Institute Malaysia, Kuala Lumpur, Malaysia; QSBG= Entomology section, Queen Sirikit Botanic Garden, Chiang Mai, Thailand; DNP= Forest Insect Collection, Forest Entomology and Microbiology Research Group, Forest and Plant Conservation Research Office, Department of National Park, Wildlife and Plant Conservation, Bangkok, Thailand; KKIC= Kasetsart Kamphaeng Saen Insect Collection, Kasetsart University Kamphaeng Saen Campus, Nakhon Pathom, Thailand; NHMUK= Natural History Museum, London, UK; NMNL= Naturalis Biodiversity Center, Leiden, the Netherlands;NHMW= Naturhistorisches Museum Wien, Vienna, Austria; PHW= Paul H. Williams research collection, UK; MJUMZ= The Museum of Zoology, Maejo University, Chiang Mai, Thailand; PCYU= The Packer Collection at York University, Canada), collection ID, subgenus and species name, collecting date (dd/mm/yyyy), year and month (Jan=January; Feb=February; Mar=March; Apr=April; May=May; Jun=June; Jul=July; Aug=August; Sep=September; Oct=October; Nov=November; Dec=December), collecting site with georeferences (latitude and longitude), elevation maximum and minimum (m), collector, and caste (Worker and Queen=Female; Male). NA= not available.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.181 | 0.065 |
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".