{"id":"W2795149741","doi":"10.1093/schbul/sby018.971","title":"S184. MACHINE LEARNING REVEALS DEVIANCE IN NEUROANATOMICAL MATURITY PREDICTIVE OF FUTURE PSYCHOSIS IN YOUTH AT CLINICAL HIGH RISK","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Deviance (statistics); Psychosis; Psychology; Developmental psychology; Psychiatry; Clinical psychology; Machine learning; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004993734,0.0001774371,0.0002074787,0.0006450152,0.0002414546,0.0003418485,0.0001979612,0.0003659694,0.005224897],"category_scores_gemma":[0.003078187,0.0001106744,0.0003192322,0.0004711656,0.0002018201,0.0002193626,0.0002426267,0.0002467344,0.000473722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002050961,"about_ca_system_score_gemma":0.0002667445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004427838,"about_ca_topic_score_gemma":0.004878371,"domain_scores_codex":[0.9998782,0.00003073871,0.00001671266,0.00003664872,0.00001469889,0.00002314099],"domain_scores_gemma":[0.9990751,0.0003357171,0.0003501777,0.0000649186,0.00008380686,0.00009028205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005089914,0.00004716883,0.9799268,0.00002119466,0.00005556776,0.0007126382,0.000107665,0.0007090683,0.003084057,0.0001999597,0.0005990928,0.01402777],"study_design_scores_gemma":[0.000009405029,0.0001185516,0.9927845,0.00001072923,0.0000210101,0.001221878,0.00006741941,0.004561173,0.00047801,0.0003913426,0.0003320238,0.000004017637],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980006,0.00008801805,0.0006080928,0.0001054367,0.000009183288,0.000007785799,0.0006803328,0.00002178951,0.0004787082],"genre_scores_gemma":[0.9990342,0.00003270791,0.0003629997,0.00001323456,0.000005272304,0.00000483896,0.0004149795,0.000005231883,0.000126658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005224897,"threshold_uncertainty_score":0.017479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02309413310002964,"score_gpt":0.2754502854072541,"score_spread":0.2523561523072245,"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."}}