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Record W2940711127 · doi:10.1038/s41380-019-0420-6

Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder

2019· article· en· W2940711127 on OpenAlexaff
Saashi A. Bedford, Min Tae M Park, Gabriel A. Devenyi, Stéphanie Tullo, Jürgen Germann, Raihaan Patel, Evdokia Anagnostou, Simon Baron‐Cohen, Edward T. Bullmore, Lindsay R. Chura, Michael Craig, Christine Ecker, Dorothea L. Floris, Rosemary Holt, Rhoshel Lenroot, Jason P. Lerch, Michael Lombardo, Declan Murphy, Armin Raznahan, Amber Ruigrok, Elizabeth G. Smith, Michael D. Spencer, John Suckling, Margot J. Taylor, Audrey Thurm, Meng‐Chuan Lai, M. Mallar Chakravarty

Bibliographic record

VenueMolecular Psychiatry · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill University Health CentreCentre for Addiction and Mental HealthHospital for Sick ChildrenUniversity of TorontoHolland Bloorview Kids Rehabilitation HospitalWestern UniversityMcGill UniversityDouglas Mental Health University Institute
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsAutism spectrum disorderPsychologySuperior temporal sulcusBrain morphometryAutismNeuroimagingNeuroscienceIntelligence quotientCytoarchitectureBrain mappingMagnetic resonance imagingClinical psychologyDevelopmental psychologyFunctional magnetic resonance imagingCognitionMedicine

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)0.001
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.040
GPT teacher head0.338
Teacher spread0.298 · 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

Citations216
Published2019
Admission routes1
Has abstractno

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