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Record W7135523857

Lateral cephalograms:why to we take them?

2022· article· en· W7135523857 on OpenAlex
Jennifer Haworth, Miesha Virdi

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

VenueExplore Bristol Research · 2022
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsInstitute of Infection and Immunity
FundersUniversity Hospital Southampton NHS Foundation Trust
KeywordsRadiographyRadiation treatment planningCephalometryIdentification (biology)Projection (relational algebra)
DOInot available

Abstract

fetched live from OpenAlex

Orthodontic indications for lateral cephalograms are diagnosis, prescription, prediction and research. Benefits of taking these radiographs must be weighed against the risks of radiation exposure. Various cephalometric analyses have been described, and these are commonly used for diagnosis and treatment planning, but unavoidable errors of both projection and identification can complicate radiographic interpretation. The use of the cervical vertebral maturation technique for growth prediction has been contentious, but may have a useful role in aiding treatment timing. Research outcomes in orthodontics have focused heavily on cephalometrics, but this is starting to change, especially with the development of 3D analysis techniques.<br/><br/>CPD/Clinical Relevance: The range of uses of lateral cephalograms in orthodontic practice and some of the latest research regarding the use of cephalometrics in treatment planning is described.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.275
GPT teacher head0.419
Teacher spread0.144 · 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