{"id":"W4311927287","doi":"10.1111/bdi.13282","title":"Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a support vector machine classifier","year":2022,"lang":"en","type":"article","venue":"Bipolar Disorders","topic":"Bipolar Disorder and Treatment","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Agence Nationale de la Recherche; Bonfils-Stanton Foundation; Israel Science Foundation; Simons Foundation","keywords":"Support vector machine; Bipolar disorder; Mood; Treatment of bipolar disorder; Mood stabilizer; Computer science; Psychology; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Machine learning; Psychiatry; Mania","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":[0.00130419,0.0005595979,0.0006611169,0.001814693,0.0002039792,0.0006240598,0.0002875778,0.0006183715,0.001040225],"category_scores_gemma":[0.004578756,0.0001257804,0.0006890449,0.0005718226,0.0001552714,0.0004432049,0.0002539217,0.0005557969,0.0003210914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003716243,"about_ca_system_score_gemma":0.0003417034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001851405,"about_ca_topic_score_gemma":0.001115685,"domain_scores_codex":[0.9995233,0.0001580125,0.00006390569,0.00009708992,0.00009883475,0.0000589691],"domain_scores_gemma":[0.9978812,0.001443969,0.0002280127,0.00007211801,0.0002908347,0.00008378083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002669845,0.0009307975,0.4292304,0.0001596825,0.0006215289,0.0003757512,0.0001678019,0.1187704,0.0128943,0.0007054108,0.003685974,0.4297882],"study_design_scores_gemma":[0.0000620423,0.0005040113,0.07620567,0.00002920944,0.0001204293,0.0001904065,0.00003707394,0.9192111,0.002515723,0.0007687858,0.0003249727,0.00003047677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.914297,0.0006702935,0.08230263,0.0003994941,0.00006965055,0.00007647924,0.00056839,0.0004292915,0.001186765],"genre_scores_gemma":[0.9834611,0.00007203455,0.01572824,0.00004767868,0.00004327403,0.00002969009,0.0004387888,0.0000101599,0.0001689054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001851405,"threshold_uncertainty_score":0.00689733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008617455268865915,"score_gpt":0.2288277358925707,"score_spread":0.2202102806237048,"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."}}