Accuracy of the DTC torque control motor for nickel‐titanium rotary instruments
Bibliographic record
Abstract
AIM: To determine the torque output and examine the accuracy of five identical DTC torque control (DTC) motors. METHODOLOGY: Torque settings on the DTC motors for the.04 ISO ProFile nickel-titanium (NiTi) rotary instruments were evaluated at 350 r.p.m. A modification of the ANSI/ADA Specification No. 28 setup for the evaluation of torsional properties of endodontic instruments was used. A handpiece was attached to the motor and gripped with a vice. An.07 Orifice Shaper, size 50, was inserted in the handpiece. The instrument tip was clamped in a chuck connected to a torque sensor. The motor was then activated to rotate the instrument in a clockwise direction until reversal of the rotation occurred. The actual torque generated at the reversal of the rotation was recorded. Ten tests were carried out at each torque setting. A new Orifice Shaper was used for each test. The means of the actual torque values generated by the motors at the different torque settings were compared with the torque values claimed by the manufacturer and analysed using analysis of variance and the Student's t-test (alpha = 0.05). RESULTS: The actual torque values were significantly higher than the torque preset on the motors (P < 0.0001) and did not differ significantly among the motors (P > 0.05). CONCLUSIONS: The actual torque deviated from the preset torque and was higher than the reported torque at fracture of several NiTi rotary instruments. The usefulness of these motors is questionable.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".