{"id":"W4360771686","doi":"10.1109/icmla55696.2022.00008","title":"Keynotes","year":2022,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Computer science","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":[0.0001128365,0.00002910652,0.0000291301,0.00003304123,0.000159797,0.00004479536,0.0005963306,0.000003939906,0.0006288378],"category_scores_gemma":[0.00001188816,0.00002794562,0.00001680257,0.0001729299,0.000005549029,0.0001032739,0.0006278115,0.00007670972,0.0001051594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002148452,"about_ca_system_score_gemma":0.00001711076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005808902,"about_ca_topic_score_gemma":9.34091e-8,"domain_scores_codex":[0.999525,0.00002312717,0.00005784426,0.00009628169,0.0001995401,0.00009824256],"domain_scores_gemma":[0.9996721,0.00003215415,0.00001866265,0.0002495945,0.000007922311,0.0000195485],"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":[2.632333e-7,0.00000479352,0.0004393276,5.5948e-7,0.000002211572,0.000003590934,0.000134688,0.7292359,0.00006663119,0.2623942,0.005146352,0.002571489],"study_design_scores_gemma":[0.00007209868,0.00006629588,0.0004055976,2.239146e-7,4.761342e-7,0.000008658392,0.00002756377,0.8580003,0.000233387,0.0008135414,0.1403047,0.00006716565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003922116,0.000007404833,0.9301216,0.0008790698,0.0002229425,0.00002784929,4.893066e-8,0.0001828954,0.06816597],"genre_scores_gemma":[0.9161437,6.999484e-7,0.06302974,0.001345955,0.00001423394,0.00001003141,7.383155e-7,0.000003054043,0.01945185],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9157515,"threshold_uncertainty_score":0.6885333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027564245858099,"score_gpt":0.208050353210398,"score_spread":0.197774710751817,"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."}}