{"id":"W2555802555","doi":"10.1002/hbm.23459","title":"Neonatal neural networks predict children behavioral profiles later in life","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Neonatal and fetal brain pathology","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"National Medical Research Council","keywords":"CBCL; Psychology; Insula; Diffusion MRI; Amygdala; Child Behavior Checklist; Tractography; Developmental psychology; Fractional anisotropy; Connectome; Neuroscience; Magnetic resonance imaging; Medicine; Functional connectivity","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.000249043,0.0002257478,0.0003488357,0.0002092712,0.0001133241,0.00001797684,0.0001607091,0.0001726729,0.000374086],"category_scores_gemma":[0.00007611427,0.0001574318,0.0001113779,0.0001557208,0.0002088564,0.0001615723,0.0001557957,0.0003067708,0.00004653666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004811529,"about_ca_system_score_gemma":0.00002578937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002677996,"about_ca_topic_score_gemma":0.00002053911,"domain_scores_codex":[0.9983774,0.00008297961,0.0003856464,0.0004445104,0.0001880393,0.0005213788],"domain_scores_gemma":[0.9993302,0.00007883136,0.00007485306,0.0002951363,0.000029272,0.0001917468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001587396,0.0001587285,0.9114586,0.00004240726,0.00003493997,0.0006196869,0.0007300552,0.0000105782,0.04099355,0.0004857848,0.002825452,0.04248149],"study_design_scores_gemma":[0.002617025,0.0003031515,0.9946407,0.0002025593,0.00001571821,0.0003123137,0.00005827168,0.0003095823,0.00007449991,0.0002422988,0.000992928,0.0002309203],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949727,0.000352867,0.0005514352,0.00278049,0.0001565519,0.0005568984,0.00001976222,0.0001530683,0.0004562323],"genre_scores_gemma":[0.9955985,0.000004776793,0.0001415015,0.001824772,0.0005693806,0.00004764415,0.00009383539,0.00003783188,0.001681747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08318214,"threshold_uncertainty_score":0.6419885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02358403036578625,"score_gpt":0.2671820276109081,"score_spread":0.2435979972451219,"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."}}