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Record W2783936185 · doi:10.15331/jdsm.6916

Prospective Assessment of Maximum Protrusion in Patients Wearing a Mandibular Advancement Device

2018· article· en· W2783936185 on OpenAlexafffund
Jean-François Massé, Audrey Bellerive, Frédéric Sériès, Laurie St‐Pierre

Bibliographic record

VenueJournal of Dental Sleep Medicine · 2018
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversité Laval
FundersInstitut universitaire de cardiologie et de pneumologie de Québec, Université Laval
KeywordsMedicineOrthodonticsDentistryProspective cohort studySurgery

Abstract

fetched live from OpenAlex

Study Objectives: Obstructive sleep apnea (OSA) is a sleep-related disorder with high prevalence in our society. The gold standard for the treatment of sleep apnea is continuous positive airway pressure (CPAP). Given the low adherence rate of patients on CPAP treatment, interest has turned toward dental appliances, commonly called mandibular advancement devices (MAD). The aim of this study was to determine whether patients' maximum protrusion could be increased after wearing a MAD for 3 months, such that patients with weak protrusion (who could at first be withdrawn from treatment) could be eligible for this treatment.

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)0.001
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 score0.015
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.021
GPT teacher head0.406
Teacher spread0.386 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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