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Record W4367303489 · doi:10.1212/wnl.0000000000203209

Whole Genome Sequencing to Resolve the Genomic Architecture of Cerebral Palsy in a Canadian Cohort (P13-9.003)

2023· article· en· W4367303489 on OpenAlexaffabout
Maryam Oskoui, Mehdi Zarrei, Worrawat Engchuan, Neal Sondheimer, Bhooma Thiruv, Edward Higginbotham, Ritesh Thapa, Tarannum Behlim, Sabrina Aimola, John T. Wei, Prakroothi Danthi, Giovanna Pellecchia, Karen J. Ho, Jill de Rijke, Jennifer Howe, Thomas Nalpathamkalam, Roozbeh Manshaei, Joseph Whitney, Rohan Patel, Omar Hamdan, Rulan Shaath, Shannon Knights, Brett Trost, Dawa Samdup, Anna McCormick, Carolyn Hunt, Adam Kirton, Anne Kawamura, Ronit Mesterman, Jan Willem Gorter, Nomazulu Dlamini, Daniele Merico, Ryan K. C. Yuen, Michael Shevell, Dimitri J. Stavropoulos, Richard F. Wintle, Darcy Fehlings, Stephen W. Scherer

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMontreal Children's HospitalMcMaster UniversityQueen's UniversityMcGill University Health CentreHolland Bloorview Kids Rehabilitation HospitalSickKids FoundationUniversity of TorontoHospital for Sick ChildrenUniversity of CalgaryChildren's Hospital of Eastern OntarioMcGill University
Fundersnot available
KeywordsConcordanceCopy-number variationGeneticsCohortCerebral palsyGenetic architecturePhenotypeExome sequencingBiologySingle-nucleotide polymorphismIndelMedicineBioinformaticsGeneGenomePathologyPsychiatryGenotype

Abstract

fetched live from OpenAlex

To capture the full extent of genomic contributions to cerebral palsy (CP) in an unselected cohort.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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