<i>Lasioglossum (Dialictus) semicaeruleum</i> (Cockerell, 1895) (Hymenoptera: Halictidae) in Maryland:A disjunct population in eastern North America?
Bibliographic record
Abstract
Since 2004, three specimens of Lasioglossum (Dialictus) semicaeruleum (Cockerell, 1895) (Hymenoptera: Halictidae) have been collected in Maryland. Other than three specimens from Wisconsin, there are no additional records of this western United States species known east of the Mississippi River. I document the three Maryland records and offer possible scenarios of how the specimens could have arrived in Maryland. Lasioglossum (Dialictus) semicaeruleum (Cockerell, 1895) (Hymenoptera: Halictidae) is an abundant western North American species that ranges from the Canadian Prairie Provinces (Alberta, Manitoba, and Saskatchewan) through the United States west of the Mississippi River (Arizona, California, Colorado, Iowa, Kansas, Minnesota, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Utah, and Wyoming) and into northern Mexico (Chihuahua, Coahuila, Durango, Nuevo León, and Sonora) (Gibbs 2010; Ascher and Pickering 2022; GBIF 2022; Fig. 1). Gibbs (2010) noted two enigmatic Maryland specimens: USGS_DRO029678, Bowie, Prince George’s County, and USGS_DRO141684, Wittman, Talbot County (Fig. 2–3) and cautioned that these might be mislabeled. In 2015, a bee survey of the Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island (hereafter Poplar Island), Chesapeake Bay, Talbot County, yielded a third Maryland specimen: USGS_DRO556278 (Fig.2).
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".