{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005062684,0.0007035172,0.001051528,0.0003096649,0.002601831,0.000100559,0.001846947,0.0009350243,0.0003536514],"category_scores_gemma":[0.003878072,0.0005478213,0.0002215282,0.001700654,0.0003108706,0.0001598136,0.0007008611,0.003017059,0.001593191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005398943,"about_ca_system_score_gemma":0.000975311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004336811,"about_ca_topic_score_gemma":0.000001410607,"domain_scores_codex":[0.9932827,0.0001652556,0.002458965,0.0008052505,0.00150812,0.0017797],"domain_scores_gemma":[0.993924,0.0008937379,0.002595748,0.0008657805,0.001077886,0.0006428435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006806051,0.001033432,0.01609062,0.01348463,0.000260548,0.000001100539,0.03009554,0.0005453449,0.009672841,0.5780547,0.3430595,0.007021071],"study_design_scores_gemma":[0.01978521,0.002291154,0.01678893,0.0231292,0.00126432,0.00007045524,0.02622873,0.02869734,0.04612022,0.03722391,0.7930757,0.005324821],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2749682,0.0002904437,0.0002068225,0.01322724,0.007355858,0.004496694,0.00003774326,0.0004335778,0.6989834],"genre_scores_gemma":[0.9811249,0.0002068351,0.00443324,0.009433882,0.0009783109,0.00007198309,0.000008858509,0.0001177445,0.003624288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7061567,"threshold_uncertainty_score":0.9996973,"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."}}