Clinical Oral Disorders in Adults Screening Protocol (CODA‐SP) from the 2019 Vancouver IADR Consensus Symposium
Bibliographic record
Abstract
BACKGROUND: The Clinical Oral Disorder in Elders (CODE) index was proposed in 1999 to assess the oral health status and treatment needs of older people who typically were edentate or had few natural teeth. Since then, more people are retaining natural teeth into old age and have oral disorders similar to younger adults. In addition, there has been further guidance on screening for disease that includes changes to the clinical indicators of several oral disorders and greater sensitivity to people's concerns about their oral health and care needs. METHODS: Experts in dental geriatrics assembled at a satellite symposium of the International Association of Dental Research in June 2019 to revise the objectives and content of the CODE index. Before the symposium, 139 registrants were asked for comments on the CODE index, and 11 content experts summarised current evidence and assembled reference lists of relevant information on each indicator. The reference lists provided the base for a narrative review of relevant evidence supplemented by reference tracking and direct searches of selected literature for additional evidence. RESULTS: Analysis of the evidence by consensus of the experts produced the Clinical Oral Disorders in Adults Screening Protocol (CODA-SP). CONCLUSIONS: The CODA-SP encompasses multiple domains of physical and subjective indicators with weighted severity scores. Field tests are required now to validate its effectiveness and utility in oral healthcare services, outcomes and infrastructure.
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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 | 0.067 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".