{"id":"W2917299178","doi":"10.1109/icra.2019.8794036","title":"Online Object and Task Learning via Human Robot Interaction","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Task (project management); Object (grammar); Computer science; Interface (matter); Human–computer interaction; Artificial intelligence; Robot; Motion (physics); Computer vision; Engineering; Systems 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001002716,0.0002336008,0.0002584396,0.0001764881,0.00006996727,0.0001129287,0.00008782464,0.0002212818,0.0003414217],"category_scores_gemma":[0.00001847235,0.0002461777,0.00006617433,0.00004957951,0.00001017832,0.0001008557,0.0001734509,0.001354015,0.0001105757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007573829,"about_ca_system_score_gemma":0.000007448335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001391862,"about_ca_topic_score_gemma":0.00007940935,"domain_scores_codex":[0.9991418,0.00004640289,0.0002578397,0.0002752878,0.000112511,0.0001662286],"domain_scores_gemma":[0.9996194,0.00002973803,0.00007159572,0.0001984763,0.00002873688,0.00005204457],"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":[0.000001613636,0.000009551038,0.001973827,0.0001728151,0.00004277685,0.000001373209,0.0002734826,0.9901503,0.003108984,0.00003128694,0.0001327189,0.004101317],"study_design_scores_gemma":[0.0001579184,0.00002418738,0.01779743,0.0001533582,0.0000223047,0.00000782898,0.0001375511,0.9777137,0.0001096552,0.00005027506,0.003504746,0.0003210376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4190416,0.0005559659,0.5438653,0.0001009267,0.002258317,0.0004805015,9.809288e-7,0.00204178,0.03165461],"genre_scores_gemma":[0.9953283,0.0000520163,0.001008945,0.00002993497,0.0002318849,0.000006009277,0.0002094076,0.00006356547,0.003069937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5762867,"threshold_uncertainty_score":0.999999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763247602429989,"score_gpt":0.2786474609535634,"score_spread":0.2510149849292634,"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."}}