{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001757134,0.0001316216,0.0002186415,0.00004583196,0.0001159204,0.0001707544,0.000191589,0.00005447034,0.00001817731],"category_scores_gemma":[0.00009349359,0.000125129,0.00006007181,0.0001466039,0.00002677534,0.0006048097,0.0001454751,0.00009199282,0.00006021377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002977407,"about_ca_system_score_gemma":0.00003593891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006702424,"about_ca_topic_score_gemma":0.00004479826,"domain_scores_codex":[0.9989398,0.000101272,0.0001515912,0.0004588231,0.0001621867,0.0001863923],"domain_scores_gemma":[0.9990253,0.0004319811,0.0001008576,0.0001535776,0.000108116,0.0001801017],"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":[0.000147532,0.0001513052,0.001331364,0.00009716174,0.00008384979,0.00001002769,0.001017739,0.000005830862,0.0101722,0.0005900075,0.003537348,0.9828556],"study_design_scores_gemma":[0.008147532,0.002253076,0.1210293,0.0002705274,0.0001029715,0.0002170132,0.0006060174,0.7502524,0.08360343,0.005336123,0.02586911,0.002312474],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07215381,0.00001467539,0.9195922,0.005953739,0.0001503724,0.0005549932,0.00003989644,0.0002516354,0.001288665],"genre_scores_gemma":[0.987009,0.000003422307,0.01181771,0.0009126591,0.0000935729,0.00009972729,0.00001193857,0.000007918752,0.00004405745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9805431,"threshold_uncertainty_score":0.5102613,"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."}}