{"id":"W2554954837","doi":"","title":"Fast and Flexible Monotonic Functions with Ensembles of Lattices","year":2016,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Monotonic function; Regularization (linguistics); Computer science; Feature (linguistics); Random forest; Artificial intelligence; Base (topology); Key (lock); Algorithm; Machine learning; Mathematical optimization; Mathematics","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":[0.0001314471,0.00008841367,0.0001162229,0.00009997498,0.0001168627,0.0002809654,0.0001750864,0.00003812609,0.000001046516],"category_scores_gemma":[0.00001202388,0.00005103692,0.00001201716,0.0002005274,0.00004988752,0.003541693,0.00003726097,0.00004379126,0.00001143531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000126862,"about_ca_system_score_gemma":0.00006726976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002512869,"about_ca_topic_score_gemma":0.000001629184,"domain_scores_codex":[0.9992789,0.00001985484,0.0002822928,0.0001051975,0.0001825487,0.0001312219],"domain_scores_gemma":[0.9993106,0.00003427871,0.0002347034,0.0001577424,0.0002133303,0.00004935857],"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":[0.00003624197,0.00002695268,0.002043476,0.0008315862,0.00002183256,8.267689e-7,0.003407445,0.006506875,0.003486308,0.02915839,0.0003313663,0.9541487],"study_design_scores_gemma":[0.0006787992,0.0002904052,0.001345092,0.0009133588,0.00001476139,0.0001324854,0.0005715212,0.989979,0.003693589,0.0003893391,0.00168288,0.0003088263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05918089,0.0001960438,0.938318,0.0003406857,0.0001059194,0.00009631354,0.000003173287,0.0001581974,0.001600747],"genre_scores_gemma":[0.9977583,0.000009408133,0.001905572,0.00004841993,0.00001536364,0.00001651186,9.497699e-7,0.000002925931,0.0002425536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.983472,"threshold_uncertainty_score":0.2709355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177979369090654,"score_gpt":0.2283673053453767,"score_spread":0.2105693684363113,"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."}}