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Record W6986810734

A quarter of a a century in craniomaxillofacial distraction osteogenesis. Where are we now; Where are we going?

2012· article· en· W6986810734 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Research Information System University of Ferrara (University of Ferrara) · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDistractionDistraction osteogenesisQuarter (Canadian coin)AirwayAirway obstruction
DOInot available

Abstract

fetched live from OpenAlex

Distraction osteogenesis has been one of the most innovative
\nconcepts in craniomaxillofacial surgery through the last 25
\nyears.
\nIn 1987 Cesar A. Guerrero first performed a mandibular
\nwidening by distraction osteogenesis. Joseph G. McCarthy in
\n1992 published an extensive paper on the treatment of hemifacial
\nmicrosomia.
\nIn 1994 Wangerin and Gropp and in 1996 Diner et al.
\npublished on the use of intraoral devices for mandibular
\ndistraction. After a quarter of century of extensive use Distraction
\nOsteogenesis has today specific indications for congenital
\ncraniofacial and cleft deformities.
\nTechnology has evolved from the first application of external
\ndevices to intraoral and hybrid or semiburied techniques.
\nIn congenital craniomaxillofacial anomalies distraction is
\nindicated during growth.
\nMandibular distraction osteogenesis can be safely and effectively
\nused to avoid or remove tracheostomy in neonates with
\nsevere airway obstruction caused by micrognatia in Pierre
\nRobin sequence.
\nThere is a great range of indications of DO in pediatric craniofacial
\ndeformities and this new concept seems to well
\ncombine the proven Tessier principle of “ first build, then
\nmove ”.
\nOn the other hand thorough Team evaluation needs to be
\nesthablished prior to the surgical decision, and the indications
\nof early distraction in neonates should be well-considered.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.826

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 head0.038
GPT teacher head0.272
Teacher spread0.234 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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