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Record W2585965516 · doi:10.1002/ajmg.a.38085

Developing a CHARGE syndrome checklist: Health supervision across the lifespan (from head to toe)

2017· article· en· W2585965516 on OpenAlexaffabout
Carrie‐Lee Trider, Angela Arra‐Robar, Conny M.A. van Ravenswaaij‐Arts, Kim Blake

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2017
Typearticle
Languageen
FieldMedicine
TopicCongenital Ear and Nasal Anomalies
Canadian institutionsDalhousie UniversityKingston General HospitalQueen's University
Fundersnot available
KeywordsChecklistReferralCHARGE syndromePsychological interventionHealth careMedicineDelphi methodPsychologyFamily medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

Health supervision and management considerations for individuals with CHARGE syndrome are often complex, and a comprehensive approach is essential. The Atlantic Canadian CHARGE syndrome team developed a checklist organized by body system and age to aid healthcare providers in their approach to the ongoing care of these individuals. The checklist was evaluated qualitatively using a modified Delphi method with widespread consultation from expert healthcare practitioners, parents, and individuals with CHARGE syndrome. These are the first comprehensive guidelines across the lifespan of CHARGE syndrome that suggest a consistent approach to medical surveillance, investigations, and management for the physician and the multi-disciplinary team caring for these individuals. We anticipate that these guidelines will provide improvements in care by preventing missed diagnoses, allowing for anticipatory counseling, and facilitating early referral for interventions and treatments. © 2017 Wiley Periodicals, Inc.

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)0.016
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.003
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 head0.049
GPT teacher head0.387
Teacher spread0.338 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations46
Published2017
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicCongenital Ear and Nasal AnomaliesFrench-language works237,207