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Record W2773909236 · doi:10.2319/071217-468.1

Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

2017· review· en· W2773909236 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Angle Orthodontist · 2017
Typereview
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSuperimpositionReliability (semiconductor)Computer scienceVoxelLandmarkSample size determinationStatisticsArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this systematic review was to synthesize the available literature concerning the reliability of three-dimensional superimposition methods when assessing changes in craniofacial hard tissues. MATERIALS AND METHODS: Four electronic databases were searched. Two authors independently reviewed potentially relevant articles for eligibility. Clinical trials, cohort, case-control, and cross-sectional studies that evaluated the reliability of three-dimensional superimposition methods on the anterior cranial base were included. RESULTS: Six studies fulfilled the inclusion criteria. Four studies used the voxel-based registration method, one used the landmark-based method and one used the surface-based method. Regarding reliability, the voxel-based studies showed on average a difference of 0.5 mm or less between images. The optimized analysis using a six-point correction algorithm in the landmark-based method showed 1.24 mm magnitude of error between images. CONCLUSIONS: Although reliability appears to be adequate, the small sample size and high risk of bias among studies make available evidence still insufficient to draw strong conclusions.

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.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.461
Teacher spread0.312 · 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