{"id":"W3090602253","doi":"10.1109/icra40945.2020.9196856","title":"PARC: A Plan and Activity Recognition Component for Assistive Robots","year":2020,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Robot; Computer science; Software deployment; Mobile robot; Activity recognition; Human–computer interaction; Component (thermodynamics); Artificial intelligence; Plan (archaeology); Assisted living; Robotics; Software 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003499273,0.00107695,0.0005296738,0.0007857037,0.0002277825,0.0005162223,0.001255432,0.0005331427,0.009245614],"category_scores_gemma":[0.001175998,0.0004058161,0.0005032497,0.0003266742,0.0002376629,0.0007180732,0.0007131168,0.0007111307,0.00470195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003689058,"about_ca_system_score_gemma":0.0008632558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005160191,"about_ca_topic_score_gemma":0.006441937,"domain_scores_codex":[0.9996763,0.00002863869,0.00002255629,0.0001198109,0.0001194647,0.00003322938],"domain_scores_gemma":[0.9995151,0.000110994,0.00005937628,0.0001108299,0.0001428231,0.00006094315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001064807,0.0005683483,0.00505207,0.00098226,0.0001651827,0.0005595232,0.0003131439,0.01770842,0.08344521,0.004584539,0.06137627,0.8241802],"study_design_scores_gemma":[0.0002376507,0.0009076765,0.01948963,0.0001362231,0.000243913,0.001361184,0.0002009969,0.6690003,0.1613269,0.006777649,0.1401338,0.0001841535],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01657203,0.0003483721,0.7894749,0.0001628755,0.0001548074,0.0007124587,0.002787763,0.1828248,0.006961966],"genre_scores_gemma":[0.2368652,0.000348826,0.7403129,0.0004839394,0.00009510828,0.0009593374,0.005276341,0.002695036,0.01296326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009245614,"threshold_uncertainty_score":0.03092963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1206842034351052,"score_gpt":0.272283677078849,"score_spread":0.1515994736437438,"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."}}