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Record W4399326744 · doi:10.11124/jbies-23-00100

Treatment outcomes in maxillofacial rehabilitation: a scoping review protocol

2024· review· en· W4399326744 on OpenAlexaff
Sreelakshmi Viswanath, S Saranya, Chandrashekar Janakiram, Suresh Nayar, Anil Mathew

Bibliographic record

VenueJBI Evidence Synthesis · 2024
Typereview
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRehabilitationProtocol (science)MedicineTreatment protocolPhysical therapyPhysical medicine and rehabilitationAlternative medicineSurgeryPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to assess the treatment outcomes following maxillofacial rehabilitation and to identify the tools used to evaluate those outcomes. INTRODUCTION: Maxillofacial defects caused due to tumor, trauma, or any pathology affects the patient physically, mentally, and psychologically. Various methodologies and strategies are used for jaw reconstruction and oral rehabilitation to help the patient regain the functions and quality of life that were lost due to the defect. The evaluation of these treatment outcomes is imperative to assess the success of rehabilitation. INCLUSION CRITERIA: The review will include patients with any maxillofacial defect caused by a developmental anomaly, trauma, or tumor. The patients must have undergone any type of reconstruction and/or rehabilitation and can be from any age group. All treatment outcomes of maxillofacial rehabilitation will be considered. Information from primary and secondary sources and from diverse geographical settings will be included. METHODS: This review will follow the JBI methodology for scoping reviews. Databases to be searched will include PubMed (Ovid), Scopus, PsycINFO (EBSCOhost), CINAHL (EBSCOhost), Web of Science, Cochrane CENTRAL, ProQuest Dissertations and Theses, and Google Scholar (first 10 pages of the search). Two independent reviewers will screen the titles and abstracts and extract data from selected studies. Data will be presented in tabular format, accompanied by a narrative summary. REVIEW REGISTRATION: Open Science Framework https://osf.io/dp8wc.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.061
GPT teacher head0.450
Teacher spread0.388 · 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.

Study designSystematic review
Domainnot available
GenreReview

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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