{"id":"W3150695153","doi":"10.1515/jcim-2020-0187","title":"A spatial-temporal study of complementary and alternative medicine (CAM) by type: exploring localization economies implications in urban areas in Ontario","year":2021,"lang":"en","type":"article","venue":"Journal of Complementary and Integrative Medicine","topic":"Complementary and Alternative Medicine Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Cluster analysis; Spatial analysis; Geography; Economic geography; Common spatial pattern; Regional science; Cartography; Data mining; Data science; Computer science; Artificial intelligence; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004393759,0.0001094957,0.0002602907,0.001533358,0.001874083,0.001085598,0.0005015722,0.0001863952,0.002318294],"category_scores_gemma":[0.00209547,0.0001898877,0.000374925,0.004983045,0.000979992,0.0005236237,0.00133055,0.0002360289,0.0001418699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01302962,"about_ca_system_score_gemma":0.0120793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.931936,"about_ca_topic_score_gemma":0.9775143,"domain_scores_codex":[0.9995143,0.00007198826,0.00003020957,0.00008448438,0.0001348578,0.0001640053],"domain_scores_gemma":[0.9983553,0.0002662168,0.000678796,0.00007255829,0.0003795258,0.0002474358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001404168,0.00003963596,0.9786217,0.0001401431,0.00004922081,0.0002238822,0.01077894,0.0002323449,0.0005697594,0.0006399825,0.000612684,0.007951293],"study_design_scores_gemma":[0.000002842564,0.00001764201,0.9896054,0.0000213567,0.00001403808,0.00003872774,0.008934602,0.0001976495,0.00004779129,0.00004938439,0.001065285,0.000005311779],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969411,0.0002318125,0.0001796475,0.0001688707,0.000002754441,0.00002804695,0.0008104187,0.000003044222,0.001634239],"genre_scores_gemma":[0.9985934,0.000190379,0.0001936806,0.00001334971,0.000001948453,0.00001746035,0.0002254212,0.000001804761,0.0007625521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06806403,"threshold_uncertainty_score":0.1369297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099720468125656,"score_gpt":0.3490954047139967,"score_spread":0.2391233579014311,"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."}}