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Record W2808515865 · doi:10.1177/1055665618780980

Presurgical Preparation of Infants With Unilateral Cleft Lip and Palate: The SAC-PP-MR Innovative Technique

2018· article· en· W2808515865 on OpenAlexaff
Ricardo Elizondo, Manuel O. Lagravère, Esthela Flores, Nora Letechipía

Bibliographic record

VenueThe Cleft Palate-Craniofacial Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVomerColumellaMedicinePremaxillaSagittal planeOrthodonticsPhiltrumHard palateDentistryOstectomyAnatomyUpper lipNoseMaxilla

Abstract

fetched live from OpenAlex

In this article, we demonstrate an effective, cheap, and fast way to shape the nasal alar cartilage in patients with unilateral cleft lip and palate. This technique straightens the vomer and brings the philtrum, columella, premaxilla, and the maxillary frenum to the midsagittal plane, while the alveolar ridges are shaped and positioned. This reduces the lip and palatal cleft to zero even in a 4-week period.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2018
Admission routes1
Has abstractyes

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