Radiographic practices of dentists undertaking endodontics in New Zealand.
Bibliographic record
Abstract
OBJECTIVES: To determine the radiographic practices of New Zealand dentists undertaking root canal treatment, and to investigate the relationship between radiographic practices and educational and clinical factors. METHODS: A questionnaire was sent to all 1200 general dental practitioners and five specialist endodontists in New Zealand. Data were subjected to descriptive and analytical statistics. RESULTS: The response rate was 79%. The mean number of root canal treatments done by general dentists in the previous 12 months was 103, and for the specialists 938. Pre-operative views were taken by 57.1% of respondents all the time and by 34.8% in most cases. The long cone paralleling and bisecting angle techniques were in regular use by similar numbers of respondents, and over one half of the practitioners regularly used film holders and electronic apex locators. Working length films were taken by 67% of practitioners all the time and by 18% in most cases. One-quarter of practitioners took a master point view all the time, and 15% did this for most cases. Almost 65% always took a film of the completed root filling and 21% did for most cases. Twenty-three per cent of practitioners did not follow up their work. CONCLUSIONS: The majority of respondents used radiographs pre-operatively, for working length assessment and to assess the final root filling. There was a general improvement in radiographic practices compared with data from a previous national survey held in 1980.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".