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Record W6950092613 · doi:10.5281/zenodo.4450839

A Study on molar incisor Hypomineralization : An overview

2019· article· en· W6950092613 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotorefractive and Nonlinear Optics
Canadian institutionsCollège Montmorency
Fundersnot available
KeywordsMolarIncisorEnamel paintGlass ionomer cementPermanent dentitionPermanent toothTooth eruption

Abstract

fetched live from OpenAlex

Molar-incisor hypomineralization is a congenital defect characterized by well demarcated enamel defects in first permanent molars and incisors presenting at the eruption of these teeth.one to all first permanent molars, and also often the permanent incisors can be affected. Diagnosis and management of this disease at an earlier stage is important because the affected teeth are prone to rapid breakdown soon after their eruption making the treatment more complicated and less successful.Aims and objectives: To review the clinical features of molar-incisor hypo mineralization and to highlight it’sdiagnostic features and clinical management in young patients. Keywords: Molar incisor Hypo mineralization, First Permanent Molars[FPMs], Post-eruption Breakdown[PEB], Glass Ionomer Cement[GIC]

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.009

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 head0.074
GPT teacher head0.311
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2019
Admission routes1
Has abstractyes

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