{"id":"W2910221532","doi":"10.1109/iros.2018.8593882","title":"Experience-Based Model Selection to Enable Long-Term, Safe Control for Repetitive Tasks Under Changing Conditions","year":2018,"lang":"en","type":"article","venue":"","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Robot; Computer science; Process (computing); Controller (irrigation); Computation; Gaussian process; Control (management); Control engineering; Artificial intelligence; Selection (genetic algorithm); Control theory (sociology); Gaussian; Engineering","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":[0.0001373816,0.0001503907,0.0001488971,0.0002047836,0.0004711816,0.0002457927,0.0004111855,0.00006164792,0.0001522595],"category_scores_gemma":[0.00003720053,0.0001342063,0.00005848806,0.0005504214,0.00006747935,0.0005355203,0.00005823712,0.00005692972,0.00006029551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007506193,"about_ca_system_score_gemma":0.0002093389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001357307,"about_ca_topic_score_gemma":0.00008954315,"domain_scores_codex":[0.9986497,0.00001766753,0.0001959509,0.0004924321,0.0001705481,0.0004737634],"domain_scores_gemma":[0.9990323,0.00006672932,0.00007091247,0.0002953348,0.0003876769,0.0001470258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009412424,0.0002255286,0.001402613,0.00007540617,0.00004626641,0.000004783444,0.003788343,0.012733,0.01578316,0.9591954,0.002641606,0.004009778],"study_design_scores_gemma":[0.000787714,0.0003976718,0.0009218969,0.0000615583,0.0000108388,0.000008888334,0.0001137402,0.9325312,0.04897882,0.01571825,0.0001488673,0.0003205051],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007902102,0.000004405719,0.9860635,0.001781608,0.0001615433,0.0004670695,0.00001376209,0.000181616,0.003424332],"genre_scores_gemma":[0.9333422,5.388185e-7,0.0603587,0.00417131,0.0001214679,0.0003143143,0.000005424859,0.000009946703,0.001676078],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9434772,"threshold_uncertainty_score":0.5472775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02258270037304342,"score_gpt":0.2944127447288588,"score_spread":0.2718300443558154,"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."}}