{"id":"W1748305042","doi":"10.1109/isit.2001.936051","title":"Information theory of multirate systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Measure (data warehouse); Class (philosophy); Computer science; Ranking (information retrieval); Element (criminal law); Linear system; Mathematics; Applied mathematics; Data mining; Mathematical analysis; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003655714,0.00009019458,0.0002288482,0.0004079448,0.00005973309,0.000309466,0.0005939194,0.00006052742,0.005522945],"category_scores_gemma":[0.004352399,0.00005678485,0.00007498002,0.000550224,0.00005424907,0.00122784,0.0001161296,0.00005788608,0.004519526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001434576,"about_ca_system_score_gemma":0.000007040929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001622705,"about_ca_topic_score_gemma":0.000001477408,"domain_scores_codex":[0.9970797,0.0002619826,0.001067441,0.0001322141,0.001310128,0.0001484848],"domain_scores_gemma":[0.9967095,0.001707981,0.0003821594,0.0006292292,0.0005070237,0.00006411225],"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":[0.00005810183,0.00008839872,0.00267005,0.00001949651,0.00001990881,0.000003207944,0.005760169,0.003012381,0.002206453,0.1263784,0.05648853,0.8032949],"study_design_scores_gemma":[0.001220254,0.00007570453,0.007573432,0.00005722247,0.000008928844,0.00002272141,0.01016292,0.7750641,0.001594636,0.01707838,0.186809,0.0003327157],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3295456,0.0003069716,0.4212651,0.00020921,0.002174335,0.0005258757,0.00003238137,0.0001375798,0.245803],"genre_scores_gemma":[0.9912282,0.000004529825,0.0022044,0.0001474728,0.00002727418,0.000004820657,7.132953e-7,0.000003903242,0.006378724],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8029622,"threshold_uncertainty_score":0.9962556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2808656407960777,"score_gpt":0.3975500633487354,"score_spread":0.1166844225526577,"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."}}