{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00339865,0.0008615128,0.001463313,0.0008045167,0.0005245844,0.001171726,0.001557467,0.001271487,0.002305802],"category_scores_gemma":[0.006178228,0.0005230333,0.0009213366,0.001134463,0.0008185734,0.001499802,0.001307402,0.002845433,0.0007778158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007472813,"about_ca_system_score_gemma":0.001308792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001440621,"about_ca_topic_score_gemma":0.001796938,"domain_scores_codex":[0.9985259,0.0006409849,0.00005121689,0.0002275504,0.0004252791,0.0001291432],"domain_scores_gemma":[0.9978289,0.001397723,0.0001258725,0.0002232207,0.000338303,0.0000860548],"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":[0.00007763279,0.0001052164,0.0009479634,0.00009630831,0.0000630673,0.00006766269,0.00007203439,0.8114957,0.001752582,0.05013619,0.003400771,0.1317848],"study_design_scores_gemma":[0.000003668067,0.00001454854,0.0000452652,0.000004303121,0.000003481246,0.000009659537,0.000002901974,0.9803205,0.0003051667,0.01872187,0.0005664114,0.000002408249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003843471,0.0001302893,0.9946316,0.0001140047,0.00002043963,0.0000260247,0.00002592235,0.0002469722,0.000961135],"genre_scores_gemma":[0.2326745,0.0003541395,0.7612092,0.0002836389,0.0001622518,0.0004109608,0.0003244544,0.0002486996,0.004332069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00339865,"threshold_uncertainty_score":0.01797402,"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."}}