{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005988362,0.0001254242,0.0001335186,0.0001764997,0.0001043585,0.0001919659,0.003926651,0.00005475783,0.000007890091],"category_scores_gemma":[0.00007666014,0.0001046383,0.0000220264,0.0008120689,0.00003992299,0.001405053,0.005635374,0.00009404881,0.00009787406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000677519,"about_ca_system_score_gemma":0.00008305463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001572542,"about_ca_topic_score_gemma":0.000006883829,"domain_scores_codex":[0.9985397,0.00005836698,0.0001796127,0.0006271877,0.0002860206,0.0003090813],"domain_scores_gemma":[0.996574,0.00003913132,0.00005477841,0.003203282,0.00002739818,0.0001013923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001300571,0.0003763111,0.002231207,0.0001122593,0.0001268873,0.000339615,0.0009805848,0.0006477496,0.002479216,0.3620527,0.4318983,0.1987421],"study_design_scores_gemma":[0.00007637122,0.0000170288,0.0004667786,0.00001638308,0.000005275065,0.00003807747,0.00003385571,0.9936598,0.0006539054,0.001465326,0.003398639,0.0001685567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01271403,0.000006687703,0.9477558,0.0002924229,0.0001115402,0.0001745777,0.00006148199,0.003197227,0.03568619],"genre_scores_gemma":[0.06474099,0.00001004748,0.9342393,0.0002061409,0.00005338928,0.000007740283,0.0003661923,0.00001482529,0.0003613573],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9930121,"threshold_uncertainty_score":0.729676,"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."}}