{"id":"W2894095668","doi":"10.1111/acps.12964","title":"Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity","year":2018,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Ministerstvo Zdravotnictví Ceské Republiky; Agence Nationale de la Recherche","keywords":"Schizophrenia (object-oriented programming); Machine learning; Artificial intelligence; Signature (topology); Psychosis; Psychology; Computer science; Pattern recognition (psychology); Psychiatry; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003105859,0.0004645765,0.0004096512,0.001112542,0.0003009602,0.0006824697,0.000365169,0.0004354589,0.0005759526],"category_scores_gemma":[0.008190163,0.000202757,0.0006822265,0.0005850677,0.0006079725,0.0006118136,0.0007216659,0.0004703556,0.0001629794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003433301,"about_ca_system_score_gemma":0.0007420933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001198019,"about_ca_topic_score_gemma":0.001940469,"domain_scores_codex":[0.9993238,0.0002747649,0.00007074489,0.0002000931,0.00008349629,0.00004702148],"domain_scores_gemma":[0.9962764,0.001757285,0.001038444,0.000522838,0.000276244,0.0001286427],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001169615,0.0003800772,0.7185655,0.0002349314,0.0007012648,0.0004330977,0.0003818964,0.05985228,0.04841115,0.001176369,0.001129914,0.1675638],"study_design_scores_gemma":[0.00008595584,0.0006321058,0.4883105,0.00007379089,0.000238422,0.0008072036,0.0001612033,0.4896156,0.01180583,0.007810063,0.0003998014,0.00005951643],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9307583,0.0001749431,0.06804797,0.0001604131,0.00001042021,0.00006397018,0.0003180408,0.0001491704,0.000316762],"genre_scores_gemma":[0.9777302,0.00005109182,0.02153445,0.00001979556,0.00001567484,0.00003675057,0.0005119613,0.00001465895,0.00008551595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9968941,"threshold_uncertainty_score":0.01642555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05515447275850306,"score_gpt":0.3596134905246516,"score_spread":0.3044590177661485,"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."}}