Comparison of the effects from coronal pre‐flaring and glide‐path preparation on torque generation during root canal shaping procedure
Bibliographic record
Abstract
This study aimed to evaluate the effect of glide-path preparation and coronal pre-flaring on torque generation of rotary nickel-titanium files. Sixty mesiobuccal root canals of 3D printed resin teeth (Dentalike) were randomly divided into 4 groups (n = 15) according to the preparation method; Group 1: OneCurve only; Group 2: OneG and OneCurve; Group 3: OneFlare and OneCurve; Group 4: OneFlare, OneG, and OneCurve. During the final canal preparation procedure, the torque generated was recorded. The sum of generated torque and maximum torque were calculated. Statistical analysis was performed with one-way ANOVA and Duncan's post hoc comparison. The summed torque was reduced by glide-path preparation and coronal pre-flaring (P < 0.05), whereas the maximum torque was not reduced by the glide-path preparation (P > 0.05). It will be advantageous to create a glide-path with coronal pre-flaring to reduce the stress and reactive forces to the NiTi file and root dentin.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".