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Comparison of the Condyle Sagittal Position of Class I and Class II Division 2 in Orthodontic Patients

2020· article· en· W3093510047 on OpenAlexfundno aff
Murilo Fernando Neuppmann Feres, Osama Eissa, Marina Guimarães Roscoe

Bibliographic record

VenueThe Journal of Contemporary Dental Practice · 2020
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsSagittal planeClass (philosophy)CondylePosition (finance)OrthodonticsDivision (mathematics)MedicineDentistryPsychologyAnatomyMathematicsComputer scienceArtificial intelligenceArithmeticEconomics

Abstract

fetched live from OpenAlex

Aim: To compare the condyle sagittal position of class I and class II division 2 in orthodontic patients. Materials and methods: Fifty orthodontic cases (30 females and 20 males; 12-31 years) from the records of an Orthodontic Graduate Program were collected. Such cases presented cone-beam computed tomography (CBCT) as part of their initial diagnostic examinations. The study sample constituted two groups, i.e. class I and class II division 2 groups. A previously calibrated examiner performed the measurements of the images, representing the distance between the condyle and the articular surface of the glenoid fossa, both anteriorly (anterior disk space-ADS) and posteriorly (posterior disk space-PDS). Descriptive statistics were performed. Data were normally distributed, and parametric tests were used. Paired sample test was used to identify differences between the right and the left joints. Differences between class I and class II/2 groups were tested using independent t test. All statistical tests were interpreted at 5% significance level. Results: When the study groups were compared in relation to the dimensions observed for the right and the left ADS and PDS, no significant differences were detected. This study also calculated the differences between right and left disk spaces within the groups, and the differences were not significant for both class I and class II/2 groups.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.053
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.410
Teacher spread0.341 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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