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Record W4385752315 · doi:10.1111/iej.13961

Quasi‐3D dynamic photoelastic analysis of stress distribution during preparation of simulated canals with 13 mechanical preparation systems

2023· article· en· W4385752315 on OpenAlexaff
Paulo Takeji Moriya, Kleber Kildare Teodoro de Carvalho, Anil Kishen, Erick Miranda Souza, Marco A. Versiani

Bibliographic record

VenueInternational Endodontic Journal · 2023
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReciprocating motionCoronal planeMaterials scienceOrthodonticsPost hocStereo microscopeMathematicsDentistryComputer scienceComposite materialMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

AIM: The aim of this study is to compare the stress produced on the internal walls of simulated canals by nine rotary and four reciprocating systems. METHODOLOGY: Sixty-five isotropic transparent blocks containing a 60° curved and tapered simulated canal were selected and distributed into 13 groups (n = 5) according to the preparation system: BioRace, HyFlex EDM, iRaCe, Mtwo, One RECI, ProTaper Next, RaCe EVO, Reciproc, Reciproc Blue, R-Motion, VDW.ROTATE, XP-Endo Rise Shaper, and XP-Endo Shaper. Each resin block was mounted in a vice and a digital camera recorded the entire sequence of each preparation system through a circular polariscope set for dark field analysis. The video frames when each instrument reached the end of the coronal, middle, and apical thirds of the canal were extracted from the recordings and analysed by two independent observers regarding the stress generated on the canal walls using a semi-quantitative evaluation on a 0-5 scale. Intra- and inter-observer agreement were subjected to the Cohen's Kappa coefficient test, whilst the experimental results were compared using Kruskal-Wallis test post hoc pairwise comparisons with Bonferroni correction (α = 5%). RESULTS: The inter- and intra-observer agreement were 0.98 and 1, respectively. Most instruments demonstrated acceptable performance (scores ≤ 2) in all thirds. Other instruments, such as the HyFlex EDM 25.12 (coronal and middle thirds), Reciproc Blue R25 and Reciproc R25 (coronal and apical thirds), R-Motion 30.04 (apical third), and VDW.ROTATE 20.05 (apical third) showed scores higher than 3. Statistical analysis revealed a significant difference amongst the tested systems at the coronal, middle, and apical thirds (p < .05). CONCLUSION: None of the canal instrumentation protocols were stress-free, showing varying levels of stress concentrations. Various factors seemed to influence the magnitude of stress and its distribution pattern on the canal walls. Overall, instruments characterized by a larger taper, lower speed, reciprocating motion, and made of heat-treated NiTi alloy exhibited higher patterns of stress distribution.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.317
Teacher spread0.305 · 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 designSimulation or modeling
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

Citations10
Published2023
Admission routes1
Has abstractyes

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