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Record W2065213113 · doi:10.1002/ajmg.a.36969

Atypical fibrodysplasia ossificans progressiva diagnosed by whole‐exome sequencing

2015· article· en· W2065213113 on OpenAlexafffund
Hao Liu, Sarah L. Sawyer, Monika Goś, David Grynspan, Kheirie Issa, Raveena Ramphal, Carmen Rotaru, Jacek Majewski, Kym M. Boycott, Gail E. Graham, Matthew Bromwich

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2015
Typearticle
Languageen
FieldMedicine
TopicHeterotopic Ossification and Related Conditions
Canadian institutionsMcGill UniversityChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersCanadian Institutes of Health ResearchOntario Genomics InstituteGénome Québec
KeywordsFibrodysplasia ossificans progressivaMedicineExome sequencingHeterotopic ossificationGenetic disorderPediatricsConnective Tissue DisorderMyositis ossificansDermatologyPathologySurgeryMutationGenetics

Abstract

fetched live from OpenAlex

Fibrodysplasia ossificans progressiva (FOP) is a rare genetic disorder characterized by congenital malformations of the great toes and progressive heterotopic ossification of connective tissue that begins during the first decade of life. Our patient presented with intrauterine growth retardation, respiratory distress, neonatal onset soft tissue masses, bilateral hallux valgus, and congenital anomalies of the thyroid and uterus. She was initially diagnosed with atypical infantile myofibromatosis based on clinical and pathological findings. She underwent whole-exome sequencing (WES) as part of the FORGE study to identify the gene for infantile myofibromatosis; however a de novo dominant mutation in ACVR1 (NM_001105.4:c.617G>A) revised the diagnosis to FOP. This patient highlights the utility of WES as an early diagnostic tool in the investigation of patients with unusual presentations of rare diseases, thereby providing clinicians with accurate molecular diagnoses and the opportunity to tailor clinical management to improve patient care.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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 designNot applicable
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

Citations11
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part ASame topicHeterotopic Ossification and Related ConditionsFrench-language works237,207