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Clinical phenotypes associated with type II collagen mutations

2011· review· en· W1701645076 on OpenAlexaff
Pekka Kannus, John F. Bateman, Ravi Savarirayan

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2011
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsSickKids FoundationHospital for Sick ChildrenQueen's University
Fundersnot available
KeywordsMedicinePhenotypeDiseaseShort statureCartilageHearing lossArthritisType II collagenMutationLegg-Calve-Perthes diseaseBioinformaticsPediatricsGeneticsPathologyGeneInternal medicineBiology

Abstract

fetched live from OpenAlex

COL2A1 mutations give rise to a spectrum of phenotypes predominantly affecting cartilage and bone from the severe disorders that are perinatally lethal to the milder conditions that are recognised in the post-natal period and childhood. The milder chondrodysplasias are characterised by disproportionate short stature, eye abnormalities, cleft palate and hearing loss. It remains poorly recognised that there is significant variability in the disease presentation, with early onset short stature conditions and later onset milder phenotypes. Similarly, it is under-acknowledged that COL2A1 mutations may solely cause joint disease in the absence of the other mentioned phenotypic clues. The underlying hypothesis is that there are novel phenotypes caused by mutations in type II collagen that extend from premature arthritis through to more severe bone dysplasias. The importance of finding a COL2A1 mutation lies in the subsequent ability to accurately assess recurrence risks and offer information regarding disease natural history. Most importantly, it enables at-risk individuals to be identified for implementation of preventative strategies and early ameliorative management of their condition. Such interventions potentially translate into a reduction in health costs associated with musculoskeletal disease.

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)0.001
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.064
GPT teacher head0.371
Teacher spread0.306 · 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

Citations95
Published2011
Admission routes1
Has abstractyes

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