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Record W2047932768 · doi:10.1002/ajmg.10234

Pseudoachondroplasia and multiple epiphyseal dysplasia: New etiologic developments

2001· article· en· W2047932768 on OpenAlexaff
Sheila Unger, Jacqueline T. Hecht

Bibliographic record

VenueAmerican Journal of Medical Genetics · 2001
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsHospital for Sick Children
FundersShriners Hospitals for Children
KeywordsCartilage oligomeric matrix proteinShort statureOsteochondrodysplasiaLocus (genetics)DysplasiaGeneticsMedicineBiologyPathologyGeneOsteoarthritisEndocrinology

Abstract

fetched live from OpenAlex

Pseudoachondroplasia (PSACH) (OMIM#177170) and multiple epiphyseal dysplasia (MED) are separate but overlapping osteochondrodysplasias. PSACH is a dominantly inherited disorder characterized by short-limb short stature, loose joints, and early-onset osteoarthropathy. The diagnosis is based on characteristic clinical and radiographic findings. Only mutations in the cartilage oligomeric matrix protein (COMP) gene have been reported in PSACH, and all family studies have been consistent with linkage to the COMP locus on chromosome 19. Multiple epiphyseal dysplasia (MED) is a relatively mild chondrodysplasia but like PSACH, MED causes early-onset joint degeneration, particularly of the large weight-bearing joints. Given the clinical similarity between PSACH and MED, it was not surprising that the first MED locus identified was the COMP gene (EDM1). Mutations causing MED have now been identified in five other genes (COL9A1, COL9A2, COL9A3, DTDST, and MATN3), making MED one of the most genetically heterogeneous disorders. This article reviews the clinical features of PSACH and MED, the known mutations, and the pathogenetic effect of COMP mutations on the cartilage extracellular matrix.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.281
Teacher spread0.264 · 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

Citations136
Published2001
Admission routes1
Has abstractyes

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