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Record W3138614239 · doi:10.1016/j.joen.2021.03.005

Endodontic Retreatment Using Dynamic Navigation: A Case Report

2021· article· en· W3138614239 on OpenAlexaff
Jonathan Bardales-Alcocer, Marco Ramírez-Salomón, Elma María Vega Lizama, María Eugenia López-Villanueva, Gabriel Alvarado-Cárdenas, Kenneth S. Serota, Jorgeraul Ramírez-Wong

Bibliographic record

VenueJournal of Endodontics · 2021
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRoot canalDentistryCrown (dentistry)MedicineCoronal planePeriodontitisOrthodontics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0060.005
Science and technology studies0.0080.005
Scholarly communication0.0050.006
Open science0.0050.005
Research integrity0.0240.010
Insufficient payload (model declined to judge)0.0040.004

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 head0.034
GPT teacher head0.338
Teacher spread0.304 · 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 designCase report
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

Citations40
Published2021
Admission routes1
Has abstractno

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