Root canals shaped by nickel-titanium instrumentation with automated computerized numerical control systems
Bibliographic record
Abstract
BACKGROUND: To investigate the efficacy of a nickel-titanium (NiTi) file with an automated computerized numerical control (CNC) system for root canal shaping. METHODS: The movement of the automated device and the insertion angle were investigated. In Experiment 1, simulated resin root canals were randomly divided into four groups (n = 20): manual downward movement using a handpiece (Group 1), vertical downward movement by CNC (Group 2), reciprocating up and down movement by CNC (Group 3), and spiral up and down movement by CNC (Group 4). In Experiment 2, five different insertion angles of the NiTi file were evaluated (n = 20). Four parameters were used to evaluate the shaping ability: change in the working length, central axis offset, curvature variation, and preparation time. Groups were compared using one-way analysis of variance (ANOVA) with significance was set at P < 0.05. RESULTS: The change in central axis position in the curved part of the root canal was found to be smaller in Group 4 than in other groups (P < 0.05). The curvature changes and preparation time of Groups 1 and 4 were significantly reduced compared with Groups 2 and 3 (P < 0.05). The variation in working length and curvature in the 5° insertion angle group was significantly smaller than in the other groups (P < 0.05). CONCLUSIONS: A spiral up and down movement, controlled by the CNC machine, and 5° insertion angle, maintained original root canal shape more precisely than other methods.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".