{"id":"W4206491640","doi":"10.1145/952576.952586","title":"SOM","year":2003,"lang":"no","type":"article","venue":"Proceedings of the 2003 ACM symposium on Applied computing - SAC '03","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Medical diagnosis; Identification (biology); Computer science; Hospital discharge; Feature extraction; Self-organizing map; Process (computing); Artificial intelligence; Narrative; Artificial neural network; Feature (linguistics); Patient discharge; Information extraction; Natural language processing; Information retrieval; Medical emergency; Medicine; MEDLINE; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000739942,0.001658268,0.001202522,0.002407721,0.001107077,0.004666775,0.002563432,0.001609136,0.0304587],"category_scores_gemma":[0.002695994,0.0005459064,0.001859535,0.00359438,0.0005840957,0.001993431,0.001867535,0.000945511,0.01451095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001321143,"about_ca_system_score_gemma":0.002269238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01926331,"about_ca_topic_score_gemma":0.02223981,"domain_scores_codex":[0.999225,0.00009867795,0.00005748593,0.0002750552,0.0002128955,0.0001308203],"domain_scores_gemma":[0.9993683,0.000143816,0.00003691661,0.00010555,0.0002926245,0.00005290916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003782608,0.0001735066,0.0036736,0.0008260267,0.0002860036,0.0002248531,0.0002100776,0.1636892,0.003586987,0.02345522,0.1023552,0.7011411],"study_design_scores_gemma":[0.00009809514,0.0001736687,0.00307456,0.000280122,0.0001430211,0.0003987813,0.0006702548,0.7276312,0.006976506,0.0686619,0.1918022,0.00008976906],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0255301,0.003574112,0.796263,0.001355088,0.001657741,0.0007822694,0.01974044,0.017584,0.1335132],"genre_scores_gemma":[0.270953,0.004625267,0.5759863,0.001389882,0.0006490817,0.001160136,0.04580758,0.002344186,0.09708454],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9695413,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08361666205133704,"score_gpt":0.3513238555876868,"score_spread":0.2677071935363498,"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."}}