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Record W4309412287 · doi:10.1111/aej.12717

Influence of rotary and reciprocating kinematics on the accuracy of an integrated apex locator

2022· article· en· W4309412287 on OpenAlexaff
Verônica de Almeida Gardelin, Júlia Itzel Acosta Moreno Vinholes, Renata Grazziotin‐Soares, Fernanda Geraldo Pappen, Fernando Branco Barletta

Bibliographic record

VenueAustralian Endodontic Journal · 2022
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsReciprocating motionApex (geometry)KinematicsPath (computing)Root canalOrthodonticsMathematicsArtificial intelligenceComputer scienceGeometryPhysicsMedicineBearing (navigation)

Abstract

fetched live from OpenAlex

We evaluated in vitro the influence of nickel-titanium instruments kinematics on the accuracy and variation of root canal working length measurements, performed with an integrated apex locator, at glide path and at the end of shaping. Forty-four mandibular incisors, included in an alginate model, were allocated at random to two groups: reciprocating and rotary. Working length was determined at glide path stage and at the end of shaping. Measurements given by the integrated apex locator were matched with visual measurements. The apex locator accuracy was based on inter-group comparison. The variation in working length was based on intra-group comparison. Kinematics influenced the accuracy of measurements only after shaping (p < 0.05), and not in the glide path (p > 0.05). Rotary had values closer to the visual measurements. Diminishing of measures occurred after shaping for reciprocating (p < 0.05); and at glide-path stage for rotary (p > 0.05). The integrated apex locator was more accurate with rotary kinematics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.269
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.033
GPT teacher head0.299
Teacher spread0.266 · 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 teacher head, 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

Citations9
Published2022
Admission routes1
Has abstractyes

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