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Record W4408343087 · doi:10.1016/j.ejwf.2025.01.003

Overcoming three-dimensional challenges through objective decomposition and virtual-digital design: A multidisciplinary case on hypodontia treatment

2025· article· en· W4408343087 on OpenAlexfundno aff
Yubohan Zhang, Haolin Zhang, Meng Meng, Jie Gao

Bibliographic record

VenueJournal of the World Federation of Orthodontists · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicdental development and anomalies
Canadian institutionsnot available
FundersSchool of Medicine, University of New MexicoFourth Military Medical UniversityRéseau de Recherche en Santé Buccodentaire et OsseuseASCLS Education and Research Fund
KeywordsHypodontiaMultidisciplinary approachMedicineDecompositionOrthodonticsDentistry

Abstract

fetched live from OpenAlex

A 15-year-old female sought multidisciplinary treatment for hypodontia, three-dimensional problems, deep overbite, multiple occlusal interferences, and collapse of the occlusion. Through virtual-digital design with objective decomposition, this patient underwent five steps of orthodontic treatment under the guidelines of the principles: removal of occlusal restriction is a prerequisite; transverse problems are solved first; then sagittal problems; and vertical correction runs through the treatment. After orthodontic and prosthetic treatment, aesthetic appearance and functional occlusion were achieved. In complex multidisciplinary cases with three-dimensional problems, which makes it difficult to formulate the final goal, virtual-digital design under objective composition and standardized comprehensive principle are effective and necessary.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.348

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 studies0.0000.000
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 head0.025
GPT teacher head0.300
Teacher spread0.275 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

Explore more

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