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Record W2761989275 · doi:10.1111/cge.13148

Axenfeld‐Rieger syndrome

2017· review· en· W2761989275 on OpenAlexafffund
Morteza Seifi, Michael A. Walter

Bibliographic record

VenueClinical Genetics · 2017
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsCraniofacialDental anomaliesGenetic heterogeneityGenetic counselingMedicineGeneticsBiologyOrthodonticsGenePhenotype

Abstract

fetched live from OpenAlex

Axenfeld-Rieger syndrome (ARS) is a clinically and genetically heterogeneous group of developmental disorders affecting primarily the anterior segment of the eye, often leading to secondary glaucoma. Patients with ARS may also present with systemic changes, including dental defects, mild craniofacial dysmorphism, and umbilical anomalies. ARS is inherited in an autosomal-dominant fashion; the underlying defect in 40% of patients is mutations in PITX2 or FOXC1. Here, an overview of the clinical spectrum of ARS is provided. As well, the known underlying genetic defects, clinical diagnostic possibilities, genetic counseling and treatments of ARS are discussed in detail.

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)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.337
GPT teacher head0.530
Teacher spread0.193 · 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
GenreReview

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

Citations165
Published2017
Admission routes2
Has abstractyes

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