{"id":"W2164092299","doi":"10.1287/opre.1060.0360","title":"Classification and Regression via Integer Optimization","year":2007,"lang":"en","type":"article","venue":"Operations Research","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Integer (computer science); Regression; Integer programming; Regression analysis; Computer science; Optimization problem; Mathematics; Mathematical optimization; Data mining; Artificial intelligence; Statistics; 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":[0.002752336,0.00007202708,0.00006378913,0.000365417,0.0006539227,0.0004083216,0.0003645027,0.00007510655,0.0000380313],"category_scores_gemma":[0.0004073575,0.00005942348,0.00001216683,0.0007983382,0.0000853634,0.0007308076,0.0001715657,0.000325952,0.00008409562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000630334,"about_ca_system_score_gemma":0.00006246378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000101738,"about_ca_topic_score_gemma":0.00010935,"domain_scores_codex":[0.9985433,0.0002376077,0.0002012133,0.0003614417,0.0004198058,0.0002366733],"domain_scores_gemma":[0.9987633,0.0001643792,0.00002021133,0.0005445896,0.0004001378,0.000107389],"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":[0.00002234328,0.0002052472,0.005286505,0.00002347493,0.00001074094,0.000004976075,0.001500619,0.01830131,0.03272191,0.4546293,0.001999539,0.4852941],"study_design_scores_gemma":[0.0001170764,0.0000570824,0.02265082,0.00001343157,8.97644e-7,0.000007967102,0.0001081066,0.9710649,0.0003807138,0.0001876358,0.005335159,0.00007622088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007286594,0.00007085413,0.9819533,0.004181333,0.00007294472,0.0001837597,8.617823e-7,0.00008907128,0.006161234],"genre_scores_gemma":[0.8714819,0.00008611541,0.1268201,0.00004483362,0.00006854746,0.00002262791,0.00006801185,0.000007263478,0.001400646],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9527636,"threshold_uncertainty_score":0.5029511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08721332552102332,"score_gpt":0.419794869743731,"score_spread":0.3325815442227077,"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."}}