{"id":"W4225540283","doi":"10.2196/35422","title":"Clustering Diagnoses From 58 Million Patient Visits in Finland Between 2015 and 2018","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Strategic Research Council; Academy of Finland","keywords":"Medical diagnosis; Medicine; Health care; Population; Cluster analysis; Cluster (spacecraft); Medical record; Medical emergency; Data mining; Family medicine; Environmental health; Computer science; Internal medicine; Pathology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001297131,0.0004938586,0.0005818271,0.005271216,0.001098,0.001027692,0.0007809466,0.0008001884,0.00153635],"category_scores_gemma":[0.006075869,0.0002489497,0.001597042,0.004210715,0.0003369545,0.0004123285,0.00129114,0.0003835482,0.0003544792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002173522,"about_ca_system_score_gemma":0.002845804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0873056,"about_ca_topic_score_gemma":0.07393208,"domain_scores_codex":[0.9982009,0.0002606259,0.000304406,0.0005441974,0.0004014995,0.0002883776],"domain_scores_gemma":[0.9979295,0.0006937986,0.0006363598,0.0001683551,0.0004098226,0.0001621855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001664836,0.0000327876,0.9788423,0.0002316761,0.0002657315,0.0006104979,0.0007702513,0.001567497,0.0003510939,0.0001646811,0.003142298,0.01385476],"study_design_scores_gemma":[0.00002246918,0.00004309772,0.9894074,0.0001174486,0.000222252,0.0005855314,0.001749335,0.004233132,0.0003804592,0.0003361616,0.002871754,0.00003094207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643693,0.001127933,0.001021755,0.0003221699,0.00005024991,0.0001019593,0.03203945,0.0000999457,0.0008673282],"genre_scores_gemma":[0.9584618,0.0005764887,0.002714155,0.00006775089,0.00004388567,0.0001345216,0.03761161,0.00001145694,0.0003784682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0873056,"threshold_uncertainty_score":0.1735948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02432955710835213,"score_gpt":0.3167981043813409,"score_spread":0.2924685472729888,"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."}}