Bibliographic record
Abstract
Deborah V. DiBenedetto, MBA, RN, COHN-S/CM, ABDA, is President of DVDiBenedetto & Associates, Ltd in New York and Senior Consultant to Medgate, Inc., in Toronto, Ontario. She is an internationally recognized expert on legal/regulatory/compliance issues, workers’ compensation, disability, healthcare cost management, integrated benefits, case/risk management, and human resources issues. Deborah is President of the American Association of Occupational Health Nurses (AAOHN); the CMSA Facilitator for the Disability/Workers’ Compensation/Occupational Health Case Management Special Interest Group; Vice President of the Hudson Valley CMSA in New York; Editorial board of the Occupational & Environment Medicine (OEM) Report; and lead author of the OEM Occupational Health & Safety Manual. Address correspondence and reprint requests to: Deborah V. DiBenedetto at DVDiBenedetto & Associates Ltd., PO Box 738, Yonkers, NY, 10710-0738 (e-mail: [email protected] or [email protected]).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.182 | 0.136 |
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".