{"id":"W2274819190","doi":"10.11575/prism/30582","title":"Using Learning of Behavior Rules to Mine Medical Data for Sequence Rules","year":2004,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Sequence (biology); Computer science; Set (abstract data type); Data mining; Artificial intelligence; Association rule learning; Operator (biology); Field (mathematics); Genetic algorithm; Machine learning; Mathematics","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":[0.002391296,0.0007101301,0.0007021551,0.00243467,0.0005400685,0.0008866378,0.001288958,0.001024866,0.0007491758],"category_scores_gemma":[0.01244774,0.0003644797,0.0009154053,0.001167507,0.0009646051,0.001137285,0.000561796,0.001131224,0.0003855969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007503697,"about_ca_system_score_gemma":0.001332403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005761563,"about_ca_topic_score_gemma":0.006813547,"domain_scores_codex":[0.9987734,0.0004078087,0.0001244815,0.0003581214,0.000281199,0.00005490872],"domain_scores_gemma":[0.9939799,0.004289916,0.0005656641,0.0004013753,0.0006536239,0.0001095564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001881419,0.0005342039,0.03814254,0.0002842714,0.0003333354,0.0005668318,0.0006977225,0.2879418,0.009587645,0.01048871,0.002278725,0.648956],"study_design_scores_gemma":[0.00002554674,0.0001374781,0.002406941,0.00006430938,0.00005411181,0.0002535796,0.0001060896,0.9680619,0.006586245,0.02035004,0.001931235,0.00002244726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06582839,0.0002853457,0.9303451,0.0005380971,0.00003159132,0.0002835813,0.0002573585,0.001109381,0.001321055],"genre_scores_gemma":[0.3238941,0.0002127364,0.6736708,0.0002058597,0.00002302726,0.0002374332,0.0008814585,0.00006848958,0.0008060068],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005761563,"threshold_uncertainty_score":0.0126465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0668885352471919,"score_gpt":0.2945799037385547,"score_spread":0.2276913684913628,"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."}}