Non-clinical information obtained by dentists during initial examinations of older adult patients
Bibliographic record
Abstract
The authors sent a questionnaire to a random sample of general dentists in Ontario, Canada, to assess the types of non-clinical information (NCI) dentists usually obtain during initial examinations of older patients. From a list of 11 NCI questions, dentists indicated which questions they usually asked during new patient examinations. The adjusted response rate was 34% (n = 672). Respondents most often asked about pain and satisfaction with the appearance of teeth and/or dentures. About half the respondents asked about oral dryness and whether problems with chewing had limited food choices. Respondents were least likely to ask about problems with speaking and avoidance of eating with others because of chewing problems. Traits of those who asked the least common NCI questions typically including continuing education courses in geriatric dentistry, self-perceived competence in treating elderly adults living in institutional settings, exposure to geriatric outreach settings during dental school and greater dentist involvement in patient history taking.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".