A review of repeat general anesthesia for pediatric dental surgery in Alberta, Canada.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to review data from the province of Alberta, Canada for First Nations children who required more than 1 general anesthesia (GA) procedure for dental surgery from 1996 to 2005. METHODS: This study was limited to First Nations and Inuit children younger than 18 years old in Alberta who received 2 or more GA procedures to facilitate dental treatment Data spanning 1996 to 2005 were provided from the Alberta Regional Office of First Nations & Inuit Health Branch, Health Canada. RESULTS: The entire database contained claims for 339 children who received repeat GA procedures for rehabilitative dental core. Seventy-six percent received 2 procedures, while the remainder underwent 3 or more surgeries. Twenty-four percent of First Nations children in this cohort were subjected to >2 GA procedures. Retreatment of previously restored teeth was a common observation. The majority of children were treated by general practitioners instead of pediatric dentists. Seventy-four percent who had 2 or more surgeries were treated by general dentists at the time of the first GA procedure. The mean age of children at the time of the first GA procedure was not associated with whether children received 2 or more GA procedures for dental care (P=.07). CONCLUSIONS: These data suggest that there may be on over-reliance on GA to treat dental caries for First Notions children in Alberta.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".