{"id":"W7047619196","doi":"","title":"Identifying ILI cases from chief complaints: comparing keyword and support vector machine methods","year":2009,"lang":"en","type":"article","venue":"NPARC","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Structured support vector machine; Identification (biology); Relevance vector machine; Field (mathematics)","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":[0.007960605,0.001099668,0.001278522,0.009729996,0.0003799177,0.001620177,0.001232444,0.002050489,0.001506948],"category_scores_gemma":[0.05082553,0.0002490511,0.0009481826,0.002908722,0.0003757781,0.002774409,0.001046433,0.0009674172,0.001681221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004512726,"about_ca_system_score_gemma":0.0009028001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003148517,"about_ca_topic_score_gemma":0.002676139,"domain_scores_codex":[0.9932394,0.00236073,0.001567239,0.0007813754,0.001589245,0.000462102],"domain_scores_gemma":[0.9399438,0.04282819,0.005704484,0.00204688,0.008041252,0.001435429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003681628,0.0007202843,0.5114942,0.001567633,0.0005296918,0.000530488,0.0008294181,0.01537871,0.006372771,0.0006608733,0.005724721,0.4525095],"study_design_scores_gemma":[0.0004307131,0.002513205,0.2377468,0.000745607,0.0006654697,0.004429808,0.003371717,0.7156405,0.02280341,0.005015194,0.006294228,0.0003433238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8251751,0.00649929,0.1522225,0.001566451,0.000474821,0.0006155132,0.006392764,0.002500138,0.004553498],"genre_scores_gemma":[0.9200411,0.0009800086,0.07307919,0.0001926199,0.0002579406,0.0001806841,0.004265099,0.00008157799,0.0009217337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009729996,"threshold_uncertainty_score":0.04210019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04473740615241265,"score_gpt":0.3544663923382743,"score_spread":0.3097289861858616,"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."}}