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Record W2595109880 · doi:10.1002/ajmg.c.31550

The Ehlers–Danlos syndromes, rare types

2017· review· en· W2595109880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Medical Genetics Part C Seminars in Medical Genetics · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsDalhousie UniversityHospital for Sick Children
FundersVlaamse regeringEhlers-Danlos SocietyEhlers-Danlos National Foundation
KeywordsJoint hypermobilityEhlers–Danlos syndromeGenetic heterogeneityMedicineConnective tissuePhenotypeNosologyDermatologyExtracellular matrixConnective Tissue DisorderPathologyGeneticsBiologyGeneAnatomy

Abstract

fetched live from OpenAlex

The Ehlers-Danlos syndromes comprise a clinically and genetically heterogeneous group of heritable connective tissue disorders, which are characterized by joint hypermobility, skin hyperextensibility, and tissue friability. In the Villefranche Nosology, six subtypes were recognized: The classical, hypermobile, vascular, kyphoscoliotic, arthrochalasis, and dermatosparaxis subtypes of EDS. Except for the hypermobile subtype, defects had been identified in fibrillar collagens or in collagen-modifying enzymes. Since 1997, a whole spectrum of novel, clinically overlapping, rare EDS-variants have been delineated and genetic defects have been identified in an array of other extracellular matrix genes. Advances in molecular testing have made it possible to now identify the causative mutation for many patients presenting these phenotypes. The aim of this literature review is to summarize the current knowledge on the rare EDS subtypes and highlight areas for future research. © 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.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0060.001
Research integrity0.0010.003
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 head0.062
GPT teacher head0.429
Teacher spread0.367 · 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