Now It's Time to Implement Social Capital and Sexually Transmitted Infection/HIV Interventions in the United States
Bibliographic record
Abstract
Department of Social and Behavioral Sciences Yale School of Public Health New Haven, CT [email protected] Department of Family Medicine and Community Health Duke University Durham, NC Conflict of Interest and Sources of Funding: The authors declare that they have no conflict of interest. Y.R. was supported by the National Institute of Mental Health under award number (K01MH111374). T.D.R. was supported by training grants from the National Institute of Mental Health (K08MH118965) and the National Institute on Minority Health and Health Disparities (U54MD012530), as well as salary support from the Duke University Center for AIDS Research, an National Institutes of Health–funded program (P30AI064518). This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Ethical Approval: This article does not contain any studies with human participants performed by any of the authors.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".