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Record W2797569268 · doi:10.1177/2380084418770662

Task Force on Design and Analysis in Oral Health Research: Medication-Related Osteonecrosis of the Jaw

2018· article· en· W2797569268 on OpenAlexfundno aff
Salvatore L. Ruggiero, Deepak Saxena, Sotirios Tetradis, Tara Aghaloo, Effie Ioannidou

Bibliographic record

VenueJDR Clinical & Translational Research · 2018
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsnot available
FundersUniversity at BuffaloGeistlich PharmaYork UniversityDivision of Cancer Prevention, National Cancer InstituteVirginia Commonwealth UniversityUniversity of South CarolinaUniversity of Connecticut Health CenterNational Cancer InstituteCase Western Reserve UniversityCleveland ClinicCleveland Clinic FoundationNational Institute of Dental and Craniofacial ResearchUniversity of PennsylvaniaNational Institutes of HealthOhio State UniversityColgate-Palmolive CompanyNational Institute of Diabetes and Digestive and Kidney DiseasesAmgen
KeywordsTask forceStatement (logic)Oral healthEtiologyMedicineTask (project management)Osteonecrosis of the jawDentistryEngineeringPolitical sciencePathology

Abstract

fetched live from OpenAlex

Knowledge Transfer Statement: This article discusses the proceedings of the conference organized by the Task Force on Design and Analysis in Oral Health Research on the understanding of the translational evidence on the etiology and pathogenesis of medication-related osteonecrosis of the jaw as well as the clinical protocols on patient management.

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)0.684
metaresearch head score (Gemma)0.640
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6840.640
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0100.012
Bibliometrics0.0100.009
Science and technology studies0.0120.016
Scholarly communication0.0150.006
Open science0.0130.020
Research integrity0.0320.047
Insufficient payload (model declined to judge)0.0120.016

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 head0.537
GPT teacher head0.599
Teacher spread0.061 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations14
Published2018
Admission routes1
Has abstractyes

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