MétaCan
Menu
Back to cohort
Record W2080401999 · doi:10.1002/ajmg.a.33045

Skeletal abnormalities in neurofibromatosis type 1: Approaches to therapeutic options

2009· review· en· W2080401999 on OpenAlexaff
Florent Elefteriou, Mateusz Kolanczyk, Aaron Schindeler, David Viskochil, Janet M. Hock, Elizabeth K. Schorry, Alvin H. Crawford, Jan M. Friedman, David G. Little, Juha Peltonen, John C. Carey, David S. Feldman, Xijie Yu, Linlea Armstrong, Patricia Birch, David L. Kendler, Stefan Mundlos, Feng‐Chun Yang, Gina Agiostratidou, Kim Hunter‐Schaedle, David A. Stevenson

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2009
Typereview
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversity of British Columbia
FundersChildren's Tumor Foundation
KeywordsNeurofibromatosisMedicineNatural historyClinical trialBioinformaticsDiseaseNeurofibromatosis type 2PathologyIntensive care medicineInternal medicineBiology

Abstract

fetched live from OpenAlex

The skeleton is frequently affected in individuals with neurofibromatosis type 1, and some of these bone manifestations can result in significant morbidity. The natural history and pathogenesis of the skeletal abnormalities of this disorder are poorly understood and consequently therapeutic options for these manifestations are currently limited. The Children's Tumor Foundation convened an International Neurofibromatosis Type 1 Bone Abnormalities Consortium to address future directions for clinical trials in skeletal abnormalities associated with this disorder. This report reviews the clinical skeletal manifestations and available preclinical mouse models and summarizes key issues that present barriers to optimal clinical management of skeletal abnormalities in neurofibromatosis type 1. These concepts should help advance optimal clinical management of the skeletal abnormalities in this disease and address major difficulties encountered for the design of clinical trials.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.168
GPT teacher head0.358
Teacher spread0.190 · 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

Citations166
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part ASame topicNeurofibromatosis and Schwannoma CasesFrench-language works237,207