{"id":"W4388426754","doi":"10.1109/ic2e59103.2023.00028","title":"REFORM: Increase alerts value using data driven approach","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Value (mathematics); Data science; Machine learning","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":[0.01111477,0.001172127,0.001380244,0.004137393,0.0006151763,0.004581406,0.002438527,0.001315394,0.00193448],"category_scores_gemma":[0.04555421,0.0006693473,0.0009483552,0.003058869,0.0008272057,0.004975103,0.002241499,0.001889593,0.0007794912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002486634,"about_ca_system_score_gemma":0.003065842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0039731,"about_ca_topic_score_gemma":0.003835414,"domain_scores_codex":[0.987323,0.003700544,0.001266477,0.001934946,0.00526971,0.0005054292],"domain_scores_gemma":[0.95793,0.01889522,0.004693241,0.005983246,0.01172033,0.0007780086],"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":[0.001368946,0.001517462,0.0552352,0.001449021,0.0004420072,0.0003891949,0.00165482,0.1374507,0.03096089,0.03903646,0.01354901,0.7169462],"study_design_scores_gemma":[0.0001364188,0.0009708219,0.012679,0.0002324381,0.0001959017,0.0002973525,0.0004866065,0.8796229,0.04674219,0.03131009,0.02716563,0.0001606539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09609322,0.0008754386,0.8749012,0.004280765,0.0002208501,0.002263445,0.003358872,0.009710199,0.008295979],"genre_scores_gemma":[0.4785389,0.0002301975,0.5153219,0.0008494515,0.0001214218,0.0006135774,0.002130152,0.0003618005,0.001832628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01111477,"threshold_uncertainty_score":0.05878121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1254642471388122,"score_gpt":0.3313830400512004,"score_spread":0.2059187929123882,"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."}}