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Periapical Inflammation Affecting Coronally-inoculated Dog Teeth with Root Fillings Augmented by White MTA Orifice Plugs

2003· article· en· W1991535792 on OpenAlexafffund
Thien‐Fah Mah, Bettina Basrani, João Miguel Santos, Elizeu A. Pascon, Leo Tjäderhane, Ghassan Yared, Herenia P. Lawrence, Sonia Friedman

Bibliographic record

VenueJournal of Endodontics · 2003
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Toronto
FundersFaculty of Dentistry, University of TorontoUniversidade de CoimbraUniversity of TorontoDalhousie University
KeywordsMineral trioxide aggregateDentistryBeagleRoot canalMedicinePulp (tooth)Body orificeAnatomy

Abstract

fetched live from OpenAlex

Placement of orifice plugs has been suggested to augment the seal of conventional root canal fillings. This study assessed in vivo the efficacy of white mineral trioxide aggregate (MTA) plugs in preventing periapical inflammation subsequent to coronal inoculation of root-filled teeth. The two-rooted mandibular premolars of six beagle dogs were conventionally prepared and filled with gutta-percha and sealer. A white MTA orifice plug was placed into one canal in each tooth. Pulp chambers were inoculated with plaque except for 12 teeth (negative control), and restored. Radiographs were taken at regular intervals. At 10 months, dogs were killed and jaw blocks processed for histology. None of the roots revealed radiographic or histologic evidence of severe inflammation. Mild inflammation was observed in 17% and 39% of the roots with and without an orifice plug, respectively (McNemar, p > 0.05). Without development of severe inflammation, the seal augmentation efficacy of MTA orifice plugs could not be determined.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.250
Teacher spread0.241 · 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 designBench or experimental
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

Citations60
Published2003
Admission routes2
Has abstractyes

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