The potential utility of an online dental research network from the operspectives of clinicians, researchers, and policy makers /
Bibliographic record
Abstract
Background. An online research network was set up among 11 dentists and 2 researchers in Montreal to test the feasibility of data collection over one year. Objectives. We evaluated the pilot participants' experiences and their perspectives regarding its potential utility. Methods. One-on-one qualitative interviews with 4 researchers, 4 dentists, and 3 policy makers. Interviews were recorded on audiotape and transcribed for coding and interpretation. Results. Although feasibility of data collection was evident in the pilot results; qualitative data revealed the limitations of the pilot, the unmet expectations, and the lack of impact of research findings. In terms of potential utility; the participants expressed interest in research, online communication and continuing education. Qualitative analysis revealed differences in perspectives and shared interests among the participants. Conclusion. An online research network can reduce the gap between research and practice. However, to attract participants, it must consider the needs and expectations of those involved.
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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 | 0.060 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".