Bibliographic record
Abstract
Hylaeus (Hylaeus) rudbeckiae (Cockerell & Casad 1895) (mesillae group) (New state record) County records: Leelanau, Keweenaw. Notes. A single male specimen from the northern LP identified by Roy Snelling and tentatively confirmed by JG is deposited at MSUC. A female record from PWRC remains uncertain due to the difficulty in distinguishing this sex from H. mesillae but is plausible given the boreal habitat present there. Although rudbeckiae is abundant in the western United States, it has only rarely been recorded from states east of the Rocky Mountains, where expected only from near the Canadian border, but identification difficulties may obscure its true status. A Wisconsin record (Mitchell, 1960) was not accepted by Wolf & Ascher (2009) but should be reevaluated as it may prove valid. Mitchell’s records from Connecticut (also reported by Hurd, 1979) are less likely to be correct, and we consider a possible New Jersey record (Hurd, 1979) to be implausible given that confirmed records in eastern North America are from boreal sites. Material examined. Leelanau Co.: Glenn Haven, 24 Aug. 1960, G.C. Eickwort (1 ♂ MSUC). Additional record. Keweenaw Co.: Isle Royale National Park, Washington Island, 47.8763 -89.2326, 16 Aug. 2013, S. Wilson (1 ♀ PWRC).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".