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Record W4385923689 · doi:10.1016/j.ajhg.2023.07.010

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies

2023· article· en· W4385923689 on OpenAlexfundno aff
Chelsea Lowther, Elise Valkanas, Jessica L. Giordano, Harold Z. Wang, Benjamin Currall, Kathryn O’Keefe, Emma Pierce‐Hoffman, Nehir Edibe Kurtas, Christopher W. Whelan, Stephanie P. Hao, Ben Weisburd, Vahid Jalili, Jack Fu, Isaac Wong, Ryan L. Collins, Xuefang Zhao, Christina Austin‐Tse, Emily Evangelista, Gabrielle Lemire, Vimla S. Aggarwal, Diane Lucente, Laura D. Gauthier, Charlotte Tolonen, Nareh Sahakian, Christine Stevens, Joon‐Yong An, Shan Dong, Mary E. Norton, Tippi C. MacKenzie, Bernie Devlin, Kelly L. Gilmore, Bradford C. Powell, Alicia Brandt, Francesco Vetrini, Michelle DiVito, Stephan Sanders, Daniel G. MacArthur, Jennelle C. Hodge, Anne O’Donnell‐Luria, Heidi L. Rehm, Neeta L. Vora, Brynn Levy, Harrison Brand, Ronald J. Wapner, Michael E. Talkowski

Bibliographic record

VenueThe American Journal of Human Genetics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsnot available
FundersNational Science Foundation Graduate Research Fellowship ProgramEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Dental and Craniofacial ResearchMicrosoftNational Human Genome Research InstituteNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Science FoundationCanadian Institutes of Health ResearchNational Research FoundationNational Research Foundation of KoreaSimons Foundation Autism Research InitiativeNational Institutes of Health
KeywordsExome sequencingAutism spectrum disorderProbandCopy-number variationGeneticsWhole genome sequencingComputational biologyDiagnostic testMicroarrayExomeBiologyMedicineGenomeBioinformaticsAutismPediatricsPhenotypeMutationGenePsychiatry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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 designSystematic review
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

Citations54
Published2023
Admission routes1
Has abstractno

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