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Record W2924877007 · doi:10.1073/pnas.1819023116

In vitro analyses of suspected arrhythmogenic thin filament variants as a cause of sudden cardiac death in infants

2019· article· en· W2924877007 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of British ColumbiaBC Children's HospitalUniversity of CalgarySimon Fraser University
FundersInstitute of Circulatory and Respiratory HealthNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Heart, Lung, and Blood InstituteAlberta InnovatesWestern Canada Research GridStem Cell NetworkCanada Research ChairsGovernment of CanadaCompute Canada
KeywordsSudden infant death syndromeIn silicoSudden cardiac deathSudden deathBiologyIn vitroGeneMedicineBioinformaticsGeneticsCardiologyInternal medicineNeurosciencePediatrics

Abstract

fetched live from OpenAlex

Significance A major aim of this study was to develop an experimental pipeline for the analysis and assessment of variants potentially causal in sudden cardiac death of infants (SCDI). The TNNI R37C +/− variant in this study was reliably and reproducibly disruptive to the normal physiology, in contrast to that in isogenic controls, across a battery of in silico and in vitro assays. This strengthens the evidence of pathogenicity and implicates a neonatal gene paralog encoding a sarcomeric contractile protein as having likely contributed to SCDI through a proarrhythmic pathway. This platform has the potential to be applied broadly as part of a standardized and clinically relevant death investigation in cases of SCDI where novel variants are identified.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.344
Teacher spread0.307 · 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