{"id":"W4380087278","doi":"10.1007/978-3-031-34586-9_28","title":"Spatio-Temporal Predictive Modeling for Placement of Substance Use Disorder Treatment Facilities in the Midwestern U.S","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Limiting; Medical prescription; Exploratory analysis; Substance use; Business; Public economics; Actuarial science; Economics; Medicine; Computer science; Psychiatry; Engineering; Data science; Nursing","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":[0.001068568,0.0003796923,0.0004019237,0.0008018677,0.0004200762,0.0009014184,0.001426771,0.0006936418,0.003056676],"category_scores_gemma":[0.003574405,0.0003748217,0.0008024215,0.001380106,0.0003167976,0.000677082,0.0007483631,0.001081512,0.0003324483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001968019,"about_ca_system_score_gemma":0.001329702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4245839,"about_ca_topic_score_gemma":0.3570797,"domain_scores_codex":[0.9997795,0.00008518112,0.00001312719,0.00007133574,0.00001576841,0.0000351266],"domain_scores_gemma":[0.9988588,0.0007877586,0.0001362303,0.0000476137,0.0001165355,0.00005298659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000191021,0.0001297867,0.2045538,0.00005348273,0.0002208431,0.0001598465,0.0001974895,0.7505845,0.0002575246,0.006354067,0.006577509,0.03072017],"study_design_scores_gemma":[0.000006892552,0.00001611704,0.01770487,0.0000222264,0.0000189953,0.00001919437,0.0002284015,0.9788006,0.00003671874,0.002561387,0.0005773339,0.000007256322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386191,0.001909902,0.03745009,0.004403706,0.0001483586,0.00004034363,0.01340333,0.0002311795,0.003793887],"genre_scores_gemma":[0.985958,0.0007007993,0.006062244,0.00009204645,0.00004233852,0.00004389145,0.004268538,0.00002056829,0.00281162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4245839,"threshold_uncertainty_score":0.8442251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06631121905786222,"score_gpt":0.2732474906634625,"score_spread":0.2069362716056003,"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."}}