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Record W2800577839 · doi:10.1177/1055665618771422

A Standardized Protocol for the Prospective Follow-Up of Cleft Lip and Palate Patients

2018· article· en· W2800577839 on OpenAlexaff
Negar Salimi, Jolanta Aleksejūnienė, Yen Edwin, Loo Angelina

Bibliographic record

VenueThe Cleft Palate-Craniofacial Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsProtocol (science)MedicineDentistryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a standardized all-encompassing protocol for the assessment of cleft lip and palate patients with clinical and research implications. METHOD: Electronic database searches were conducted and 13 major cleft centers worldwide were contacted in order to prepare for the development of the protocol. In preparation, the available evidence was reviewed and potential fistula-related risk determinants from 4 different domains were identified. RESULTS: No standardized protocol for the assessment of cleft patients could be found in any of the electronic database searches that were conducted. Interviews with representatives from several major centers revealed that the majority of centers do not have a standardized comprehensive strategy for the reporting and follow-up of cleft lip and palate patients. The protocol was developed and consisted of the following domains of determinants: (1) the sociodemographic domain, (2) the cleft defect domain, (3) the surgery domain, and (4) the fistula domain. CONCLUSION: The proposed protocol has the potential to enhance the quality of patient care by ensuring that multiple patient-related aspects are consistently reported. It may also facilitate future multicenter research, which could contribute to the reduction of fistula occurrence in cleft lip and palate patients.

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)0.001
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 score0.061
Threshold uncertainty score0.642

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 studies0.0010.001
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 head0.020
GPT teacher head0.321
Teacher spread0.300 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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