Failure of ProFile Ni-Ti instruments used by an inexperienced operator under access limitations
Bibliographic record
Abstract
AIM: The purpose of this study was to evaluate the failure incidence of ProFile nickel-titanium rotary instruments (PRI) when used by an inexperienced operator in conjunction with different motors and under limitations of access. METHODOLOGY: PRI with 0.06 taper were used by an inexperienced operator in a crown-down technique. The teeth were mounted in resin arches of a phantom head to reproduce limitations of access. In groups 1-4, air, high torque control, low torque control and very low torque control motors were used, respectively. Each group included 30 canals in extracted human molars. One set of PRI sizes 40-15 was used for each canal; the PRI were sterilized before each case. A 2.5% NaOCl solution was used as an irrigant. An inexperienced operator performed all the cleaning and shaping procedures after application of a rubber dam. The opening of the mouth in the phantom head was standardized for the four groups. The number of deformed and separated instruments was recorded for the various experimental groups and analyzed statistically for significance with chi-square tests. RESULTS: A high incidence of instrument deformation and separation occurred with the air, high torque control and low torque control motors. Only seven and two instruments deformed and separated, respectively, with the very low torque control motor, whereas at least 23 and 10 instruments deformed and separated respectively with the other motors. CONCLUSIONS: A very low torque control motor was safer than on air, high torque control or low torque control motors when PRI with 0.06 taper were used by an inexperienced operator in a crown-down manner at 170 rpm.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".