{"id":"W4411022335","doi":"10.1145/3742796","title":"Gradient Boosted Programming for Low Cardinality Classification","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Evolutionary Learning and Optimization","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cardinality (data modeling); Computer science; Artificial intelligence; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002925416,0.0001357543,0.0001315694,0.000232065,0.0009167998,0.000112196,0.0002146748,0.00008791663,0.000005474339],"category_scores_gemma":[0.0001495403,0.0001404611,0.00007849212,0.0005151661,0.00004618748,0.0002677076,0.00001211988,0.0002596948,0.000002511478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009249715,"about_ca_system_score_gemma":0.00006694438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001828213,"about_ca_topic_score_gemma":0.000001781682,"domain_scores_codex":[0.9988717,0.0001434711,0.0002144202,0.0004233604,0.0001444761,0.0002026124],"domain_scores_gemma":[0.9991957,0.0002249111,0.00008356958,0.0002823486,0.0001574077,0.00005608092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002888832,0.00009004724,0.0003772178,0.00003751124,0.0000272571,2.817562e-7,0.0001295705,0.7352483,0.00001547117,0.002490808,0.00004845515,0.2615062],"study_design_scores_gemma":[0.0004475388,0.000176809,0.002525171,0.00006006541,0.00002598855,0.000005268397,0.00008734623,0.9864388,0.0000275129,0.000639894,0.0094257,0.0001399777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005906331,0.0001949918,0.9954191,0.002577557,0.000300267,0.0003209235,0.000003216704,0.000369983,0.0002233276],"genre_scores_gemma":[0.4649794,0.0001174454,0.5327802,0.00008736325,0.00003601622,0.0001718594,0.00006085676,0.00001115277,0.001755727],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4643888,"threshold_uncertainty_score":0.7051376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223234041435819,"score_gpt":0.270142507485868,"score_spread":0.2579101670715098,"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."}}