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Record W2021273501 · doi:10.1097/blo.0b013e3181334b51

Evaluation of the Anatomic Burden of Patients with Hereditary Multiple Exostoses

2007· article· en· W2021273501 on OpenAlexaff
Christine M. Alvarez, Mary A. De Vera, Tim R Heslip, Brett Casey

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2007
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsHereditary multiple exostosesMedicineExostosisOsteochondromaDeformityGenotypeLesionSurgeryInternal medicineGeneticsGeneBiology

Abstract

fetched live from OpenAlex

Hereditary multiple exostosis (HME) is an autosomal dominant condition resulting predominantly from mutations in the exostosin 1 (EXT1) and exostosin 2 (EXT2) genes. We asked two questions in our study: first, what is the anatomic burden of subjects with HME; second, is there a difference in anatomic burden in subjects with EXT 1 versus EXT 2. The anatomic burden experienced by HME patients was defined according to three domains: (1) lesion quality; (2) limb malalignment and deformity; and (3) limb segment lengths and percentile height. Seventy-nine subjects with HME were included in this study. Of these 79 phenotypes were completed. Forty-eight genotypes were confirmed leaving 48 complete genotype-phenotype profiles for analysis. Analysis of the coding and flanking intronic regions of EXT1 and EXT2 was performed in each patient by direct sequencing of PCR-amplified genomic DNA. All three domains of anatomic burden showed a wide range of presentation in the HME study sample. More lesions and greater tendency to flat bone occurrence was associated with EXT1. EXT1 patients were shorter. All limb segments tended to be shorter for EXT1 subjects. EXT1 subjects showed more anatomic burden with respect to lesion quality and height.

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 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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.094
GPT teacher head0.424
Teacher spread0.330 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations54
Published2007
Admission routes1
Has abstractyes

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