A Framework for Assessing Oral Healthcare Programs in Residential Care Facilities
Bibliographic record
Abstract
There is no gold standard of oral healthcare for people who are old and frail. Traditional biological measurements of treatment outcomes, such as dental status, are insufficient to reflect the complexity of oral care programs in residential facilities for elders. A comprehensive and meaningful assessment attends to the quality of care consistent with existing evidence along with professional knowledge and standards. Two similar protocols or frameworks are available to guide the assessment of oral care programs in residential care: the Quality Assurance - Health Program Evaluation (QA-HPE) based on concepts of quality of care and health technology assessment, and the Oral Health Care Track derived from the PRECEDE/PROCEED model of health promotion. Both protocols can identify what is necessary for planning and implementing a program to increase quality of care by assessing the effects on behaviors and related risks to the recipients and care providers.
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 | 0.040 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.014 | 0.008 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".