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Record W4283801014 · doi:10.29309/tpmj/2022.29.07.6914

Frequency of congenitally missing third molars in orthodontic patients.

2022· article· en· W4283801014 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 Professional Medical Journal · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicdental development and anomalies
Canadian institutionsAbbott (Canada)
Fundersnot available
KeywordsMedicineMolarMaxillaDentistryMandible (arthropod mouthpart)OrthodonticsPanoramic radiographSignificant differenceRetrospective cohort studyRadiographySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Objective: To determine the frequency of congenitally missing third molars in Orthodontic patients. Study Design: Retrospective Study. Setting: Department of Orthodontics at Abbottabad International Dental College, Abbottabad. Period: February 2021 to November 2021. Material & Methods: Retrospective data was collected from the files in the departmental archives. Files from the past seven years were studied for data collection. Congenitally missing teeth were identified from the patient’s history and the Orthopantomogram present within each file. The collected data was analyzed via SPSS software Version 21. Results: Chi-square test was applied to find the frequency of missing teeth. Congenital absence of third molars was highly significant among maxilla and mandible (p-value <0.001). No significant difference was found among the genders. Conclusion: Congenitally missing third molars are more prevalent in the maxilla than the mandible.

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)0.001
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 score0.060
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.262
Teacher spread0.254 · 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