{"id":"W2133720322","doi":"10.1002/9780470012505.tad028","title":"Discretization of Distributions","year":2004,"lang":"en","type":"other","venue":"Encyclopedia of Actuarial Science","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Discretization; Simple (philosophy); Distribution (mathematics); Applied mathematics; Mathematics; Aggregate (composite); Computer science; Order (exchange); Discretization of continuous features; Discretization error; Algorithm; Mathematical optimization; Mathematical analysis; Materials science; Nanotechnology","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":[],"category_scores_codex":[0.001092936,0.000149703,0.0003470319,0.0005796768,0.0001054809,0.0000489423,0.001447798,0.0001571223,0.002209997],"category_scores_gemma":[0.00262702,0.0001136276,0.0001144909,0.002561695,0.001139588,0.0001821091,0.0001785481,0.0000971067,0.00006570932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005807543,"about_ca_system_score_gemma":0.0006998391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004058226,"about_ca_topic_score_gemma":0.00004395984,"domain_scores_codex":[0.99686,0.00003350491,0.0007214549,0.0004836429,0.001707473,0.0001939569],"domain_scores_gemma":[0.9974664,0.0002529245,0.0009511752,0.0008564153,0.0003679018,0.0001051364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001254174,0.0002313163,0.001006169,0.00001975936,0.00001175916,4.814825e-7,0.0004273278,0.0002006951,0.001415313,0.7625543,0.1980684,0.03605183],"study_design_scores_gemma":[0.0002074251,0.00005617252,0.00236527,0.00008776179,0.00002126168,6.780832e-7,0.00005439307,0.00008799943,0.002207545,0.05719047,0.9375135,0.0002075442],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0002401223,0.00004288818,0.1141449,0.000177618,0.000443034,0.0004091975,0.0003183853,0.00007372351,0.8841501],"genre_scores_gemma":[0.5419024,0.0005273914,0.02935862,0.00003153118,0.0008261688,0.00006458921,0.0001326717,0.0001588353,0.4269978],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.739445,"threshold_uncertainty_score":0.9987021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03328963449778183,"score_gpt":0.3810483176375809,"score_spread":0.3477586831397991,"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."}}