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Record W4404394460 · doi:10.3389/fvets.2024.1499465

A micro-CT study of the pulp cavity morphology of maxillary fourth premolar teeth in dogs

2024· article· en· W4404394460 on OpenAlexfundno aff
Marie-Christine Morin

Bibliographic record

VenueFrontiers in Veterinary Science · 2024
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
FundersInstitut universitaire de cardiologie et de pneumologie de Québec, Université Laval
KeywordsPulp (tooth)Coronal planePremolarDentistryRoot canalOrthodonticsCanine toothMedicineAnatomyMolar

Abstract

fetched live from OpenAlex

Introduction: The objectives of the present study were (1) to describe the anatomy of the endodontic system of the dog's maxillary fourth premolar tooth (MxPM4) in relation to the morphology of the crown, (2) to determine if variations of the endodontic system exist, and (3) to look at the implications for endodontic treatment. Methods: Ten MxPM4 were harvested en bloc and scanned using micro-computed tomography (micro-CT). Results: The morphology of the pulp chamber mostly corresponded with the shape of the crown. Three pulp horns were clearly visible and related to the paracone, the metacone, and the metastyle. Nevertheless, the pulp horns of the metacone and metastyle could be fused, partially fused or distinct. Other pulp projections were also present, but rarely, in the parastyle, the protocone, and the plesioconule. All teeth showed a noticeable angulation of an average of 150 degrees at the coronal third of the mesiopalatal canal. Discussion: Thus, the most common transcoronal approach for root canal treatment does not allow a straight access to the apex. There were also minor variations in the locations of the canal orifices. This first micro-CT study of the MxPM4 in dogs showed anatomical features and variations of the pulp cavity that have not been described before.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.298
Teacher spread0.273 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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