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Record W4211166653 · doi:10.1093/ehjcr/ytac063

A previously undescribed pathogenic variant in FBN1 gene causing Marfan syndrome: a case report

2022· article· en· W4211166653 on OpenAlex
Asem Suliman, Weiang Yan, Michael H. Yamashita, Anthony D. Krentz, Aizeddin Mhanni, Philip J. Garber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Heart Journal - Case Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsUniversity of ManitobaMcMaster University
Fundersnot available
KeywordsMarfan syndromeFibrillinMedicineGenetic testingAortic dissectionGenetic diagnosisConnective tissueGeneGenetic counselingIntervention (counseling)BioinformaticsIntensive care medicineGeneticsPathologyInternal medicineBiologyAorta

Abstract

fetched live from OpenAlex

Background: Marfan syndrome (MFS) is an autosomal dominant multisystem connective tissue disorder with increased risk of aortopathy with a high risk of subsequent life-threatening aortic dissection. Diagnosing this condition is reliant on recognizing clinical features and genetic testing for confirming diagnosis, using the revised Ghent criteria. Case summary: ), designated c.7016G>C. Prior to identifying the new gene variant, this patient did not meet the revised Ghent criteria for MFS diagnosis. We present clinical and molecular evidence supporting the likely pathogenic nature of this variant, leading to earlier therapy and intervention. Discussion: The discovery of a new pathogenic gene will expand the current aortopathy and MFS database and may lead to more informed clinical management decisions for the timing and nature of interventions.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.038
GPT teacher head0.313
Teacher spread0.274 · 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