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Record W3215218015 · doi:10.51985/jbumdc2018028

Maxillary Intermolar Width Of Pakistanis With Untreated Normal Occlusion

2018· article· en· W3215218015 on OpenAlex
Muhammad Azeem, Arfan Ul Haq, Javed Iqbal, Asif Iqbal, Waheed Ul Hamid

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

VenueJournal of Bahria University Medical and Dental College · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsCollège Montmorency
Fundersnot available
KeywordsPremolarMedicineOcclusionOrthodonticsDentistryArchSurgeryMolarEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Objective: Intermolar width is a key measurement which assists in treatment planning of orthodontic patients requiring expansion as an alternate to premolar extraction. The present research was aimed at determining the mean value of intermolar arch width (IMW) of untreated normal arch Pakistani patients visiting tertiary care dental hospital Material & Methods: This cross sectional study was carried out using IMW measurements on plaster model of 120 untreated normal occlusion patients, at Department of Orthodontics, Faisalabad Medical University and de’Montmorency College of dentistry, from 15-12-2016 to 15-10-2017. The non probability consecutive sampling technique was used in this study. Data analysis was done using SPSS software 21.0.0. Results: The mean age of the subjects was 18.23±3.75 years. The mean value of IMW in selected subjects was 45.33±3.42 mm. Conclusion: Study results concluded that in Pakistanis, ideally align maxillary arch and occlusion can be achieved with upper intermolar distances of 45.33±3.42 mm

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.998

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.360
Teacher spread0.344 · 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