{"id":"W1810238482","doi":"10.1016/j.pediatrneurol.2015.06.013","title":"Structural Gray Matter Differences During Childhood Development in Autism Spectrum Disorder: A Multimetric Approach","year":2015,"lang":"en","type":"article","venue":"Pediatric Neurology","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; University of Toronto; Montreal Neurological Institute and Hospital; McGill University; Glenrose Rehabilitation Hospital; Holland Bloorview Kids Rehabilitation Hospital; International Laboratory for Brain, Music and Sound Research","funders":"Canadian Institutes of Health Research; Children Neurodevelopmental Disorders Network","keywords":"Autism spectrum disorder; Psychology; Neuroscience; Autism; Prefrontal cortex; Voxel-based morphometry; Gray (unit); Neurodevelopmental disorder; Temporoparietal junction; Inferior frontal gyrus; White matter; Magnetic resonance imaging; Developmental psychology; Functional magnetic resonance imaging; Medicine; Cognition","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002395538,0.0003947007,0.0004569631,0.001398416,0.0002177467,0.00007961675,0.0008912878,0.0001809041,0.0001843745],"category_scores_gemma":[0.0002971237,0.0003528422,0.00006898061,0.002191602,0.0001486015,0.0002360111,0.0006005802,0.0009088606,0.0005342618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007819245,"about_ca_system_score_gemma":0.0002188756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002122787,"about_ca_topic_score_gemma":0.00008369721,"domain_scores_codex":[0.9957444,0.0005059689,0.000560722,0.001187172,0.0007135331,0.001288193],"domain_scores_gemma":[0.9988477,0.0002395265,0.0001693084,0.0004390111,0.000005822023,0.0002986756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008391553,0.0002909022,0.9970634,0.00003226166,0.000003360994,0.000125484,0.001128227,0.0001495257,0.00007915469,0.0007397773,0.00003300264,0.0002710131],"study_design_scores_gemma":[0.001909115,0.0001609543,0.9925026,8.649948e-7,0.000007852128,0.0002053136,0.00001294224,0.001093877,0.0003641135,0.003308049,0.0000675928,0.0003666879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935735,0.0003062409,0.00008147132,0.003697651,0.0003719132,0.0006594167,0.000006315974,0.0001503921,0.001153101],"genre_scores_gemma":[0.9988875,0.00008245448,0.0002190918,0.000336691,0.0001293091,0.0001113972,0.000004557585,0.0000553902,0.0001736034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005314008,"threshold_uncertainty_score":0.9998924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02460522739959972,"score_gpt":0.2489319622319172,"score_spread":0.2243267348323175,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}