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Record W4415831471 · doi:10.1016/j.identj.2025.104941

Sc In Large Apical Sizes Of Permanent Teeth With Cap

2025· article· en· W4415831471 on OpenAlexaboutno aff
Gong Qimei, Jiang Hong-wei, Liao Zekai

Bibliographic record

VenueInternational Dental Journal · 2025
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRoot canalPermanent teethEndodonticsApical foramenApicoectomyGutta-perchaRoot resorptionRadiography

Abstract

fetched live from OpenAlex

Introduction The endodontic treatment of root canals with large apical sizes is considered one of the most complex challenges for clinicians. This case series evaluated the clinical outcome of single-cone (SC)obturation technique with iRoot SP in root canals with large apical sizes in chronic apical periodontitis(CAP). Case description The teeth with large apical sizes and CAP were treated. After access preparation and establishing apical patency, root canal preparation and disinfection were performed. IRoot SP(Innovative Bioceramix Inc., Vancouver, Canada)assisted gutta percha tip filling root canal. Radiography was performed to check the root canal obturation. The access cavity was sealed with GIC or composite resin. The treated teeth were followed up for at least two years. Discussion Clinical evaluation during the follow-up period revealed the significant healing of periapical lesions. After 2 years, teeth were asymptomatic and tested negatively in all clinical tests. Radiographs showed no further progression of resorption and healing of the periapical tissues. Conclusion/clinical significance Cases in this report show the effectiveness of SC with iRoot SP for treating large apical sizes in permanent teeth with chronic apical periodontitis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.008
GPT teacher head0.301
Teacher spread0.293 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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