{"id":"W2744444471","doi":"10.1002/cjs.11330","title":"Online updating method with new variables for big data streams","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Cancer Institute","keywords":"Computer science; Data stream mining; Big data; Data stream; Context (archaeology); Data mining; Set (abstract data type); Data set; Linear regression; Algorithm; Machine learning; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006325534,0.0001196342,0.0002211296,0.0001432608,0.000332151,0.0007263304,0.003863299,0.00004080649,0.000006726264],"category_scores_gemma":[0.001604916,0.0001015384,0.00001524935,0.00006466945,0.00007089252,0.0006992554,0.0001788251,0.0001627277,7.359442e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006480764,"about_ca_system_score_gemma":0.003546098,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01423008,"about_ca_topic_score_gemma":0.07791575,"domain_scores_codex":[0.998998,0.00002553909,0.0003106615,0.0002133807,0.0001654969,0.0002869002],"domain_scores_gemma":[0.9966996,0.0002881923,0.0006579699,0.001500343,0.0002923286,0.0005615367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005261143,0.0000125361,0.001197619,0.00001584441,0.00005665769,0.0001786991,0.0001360419,0.00001821803,0.00001193963,0.03996838,0.1800518,0.778347],"study_design_scores_gemma":[0.003670872,0.00267567,0.01428446,0.001461996,0.0004829268,0.002075842,0.0004834562,0.1388573,0.001179644,0.2083063,0.6249704,0.001551093],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001039619,0.00003605988,0.9929419,0.000871092,0.000453381,0.00007781299,0.005300081,0.00001288244,0.0002028442],"genre_scores_gemma":[0.005022185,0.000009531899,0.9940924,0.0001332886,0.0004616572,5.654611e-7,0.0001633131,0.00001541418,0.0001016238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7767959,"threshold_uncertainty_score":0.9923342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1247159512766345,"score_gpt":0.3397142720643705,"score_spread":0.214998320787736,"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."}}