{"id":"W1979610727","doi":"10.1145/1645953.1646065","title":"Mining data streams with periodically changing distributions","year":2009,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Data stream mining; Computer science; Data mining; STREAMS; Matching (statistics); Reuse; Focus (optics); Dynamism; Class (philosophy); Artificial intelligence; Mathematics; Statistics; Engineering","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":[0.0001572579,0.00008097559,0.0001029214,0.00005476567,0.0002782889,0.0002981407,0.0008832692,0.00001827208,0.00005765983],"category_scores_gemma":[0.00002039032,0.00005666646,0.00002274271,0.0005653852,0.0000242234,0.0005874608,0.0002919776,0.00005040332,0.00001079108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001075446,"about_ca_system_score_gemma":0.00003363717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001333949,"about_ca_topic_score_gemma":0.00002520576,"domain_scores_codex":[0.9991308,0.000009682941,0.0001191626,0.0003129843,0.0001605068,0.0002668398],"domain_scores_gemma":[0.9990575,0.0000170913,0.00004490983,0.0007680923,0.00003630916,0.00007608286],"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":[0.000004327445,0.00007622208,0.000874093,0.000002546825,0.00003831799,0.00003814402,0.0008009668,0.0001671652,0.0001477629,0.1318041,0.001285894,0.8647605],"study_design_scores_gemma":[0.0001975368,0.0002098806,0.00264122,0.00003349176,0.00002392523,0.00005121469,0.0005881459,0.9836604,0.0001775123,0.0002254246,0.0119195,0.000271715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01619413,0.00003277626,0.9732813,0.00204465,0.00001868725,0.00003142495,0.000007237903,0.0001422712,0.00824748],"genre_scores_gemma":[0.8364013,0.000002009187,0.1629155,0.0001432055,0.00004239887,6.688621e-7,0.00005558488,0.000002170083,0.0004371238],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9834933,"threshold_uncertainty_score":0.2874977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02408277999409109,"score_gpt":0.2397709356912477,"score_spread":0.2156881556971567,"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."}}