An Assessment of Direct Restorative Material Use in Posterior Teeth by American and Canadian Pediatric Dentists: I. Material Choice.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to assess the preferences of pediatric dentists in Canada and the United States about clinical decision-making related to the placement of direct restorative materials. METHODS: A cross-sectional web-based survey was used to collect the preference of all active pediatric members of the Royal College of Dentists of Canada and the American Academy of Pediatric Dentistry on the use of direct restorative materials in posterior teeth in healthy, developmentally delayed (DD), and medically compromised (MC) children. Bivariate and multivariate analyses were performed to determine the association between the predictor variables and all materials at two-tailed P<0.05. RESULTS: A response rate of 19.3 percent (n equals 762) was achieved. For DD patients, stainless steel crowns were the most preferred material for primary teeth, and a similar frequency of amalgam and composite were preferred for permanent teeth. Amalgam usage was increasingly preferred in the DD population versus healthy and MC patients. CONCLUSIONS: Composite resin was the most preferred restoration for Class I, II, and V restorations in primary and permanent teeth in healthy and medically compromised individuals. In DD individuals, stainless steel crowns and amalgam were preferred more frequently.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".