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Influence of rotational speed, torque and operator’s proficiency on ProFile failures

2001· article· en· W2114677888 on OpenAlexaff
Ghassan Yared, Fadia E. Bou Dagher, Pierre Machtou

Bibliographic record

VenueInternational Endodontic Journal · 2001
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRotational speedMathematicsTorqueMolarSignificant differenceStatistical significanceMaterials scienceOrthodonticsDentistryStatisticsMedicinePhysicsMechanical engineeringEngineering

Abstract

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AIM: The purpose of this study was to evaluate the influence of rotational speed, torque, and operator experience with a specific Ni-Ti rotary instrumentation technique on the incidence of locking, deformation and separation of instruments. METHODOLOGY: ProFile Ni-Ti rotary instruments (PRI) sizes 40-15 with a 6% taper were used in a crown-down technique. In one group of canals (n = 300) speeds of 150, 250 and 350 rpm (subgroups 1, 2 and 3) were used. Each one of the subgroups included 100 canals. In a second group (n = 300) torque was set at 20, 30 and 55 Ncm (subgroups 4, 5 and 6). In the third group (n = 300) three operators with varying experience (subgroups 7, 8 and 9) were also compared. Each subgroup included the use of 10 sets of PRI and 100 canals of extracted human molars. Each set of PRI was used in up to 10 canals and then sterilized before each case. NaOCl 2.5% was used as an irrigant. The number of locked, deformed, and separated instruments for the different groups, and within each part of the study was analysed statistically for significance with chi-squared tests. RESULTS: In group 1 only one instrument was deformed in the 150-rpm group and no instruments separated or locked. In the 250-rpm group instrument separation did not occur, however, a high incidence of locking, deformation and separation was noted in the 350-rpm group. In general, instrument sizes 30-15 locked, deformed and separated. Chi-squared statistics showed a significant difference between the 150 and 350 rpm groups but no difference between the 150 and 250 rpm groups with regard to instrument separation. Overall, there was a trend toward a higher incidence of instrument deformation and separation in smaller instruments. Locking and separation occurred during the final passage of the instruments, in the last (tenth) canal in each subgroup. In the second group, neither separation nor deformation and locking occurred during the use of the ProFile instruments, at 150 rpm, and at the different torque values. In the third group, chi-squared analysis demonstrated that significantly more instruments separated with the least experienced operator. Instrument locking, deformation, and separation did not occur with the most experienced operator. CONCLUSIONS: Preclinical training in the use of the PRI technique with crown-down at 150 rpm were crucial in avoiding instrument separation and reducing the incidence of instrument locking and deformation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.293
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations182
Published2001
Admission routes1
Has abstractyes

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