{"id":"W3082017561","doi":"10.1109/embc44109.2020.9175610","title":"Learning-Aided User Intent Estimation for Smart Rollators","year":2020,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Reliability (semiconductor); Computer science; Encoder; Estimation; Inertial measurement unit; Population; Artificial intelligence; Machine learning; Simulation; 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":[0.0001965736,0.0001019041,0.0001577072,0.00005089006,0.00008597418,0.0001808088,0.0002985455,0.00004397439,0.00004678486],"category_scores_gemma":[0.0003498376,0.00009376765,0.00008765717,0.0002365771,0.00001104219,0.000600326,0.0001208798,0.00009035572,0.0003317038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003234778,"about_ca_system_score_gemma":0.00004178365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003076581,"about_ca_topic_score_gemma":0.0000125312,"domain_scores_codex":[0.9990708,0.00005946524,0.0002142453,0.0003159019,0.0001783152,0.0001612268],"domain_scores_gemma":[0.9992611,0.0002057237,0.00009176372,0.0001705748,0.0001506272,0.0001201748],"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":[0.0001303301,0.000149079,0.01138002,0.0001836241,0.0001776316,0.000009093101,0.007363748,0.00311902,0.005572722,0.0207434,0.0421565,0.9090148],"study_design_scores_gemma":[0.000605299,0.0002622869,0.0009361051,0.00001716602,0.000006821445,0.000007189511,0.000147223,0.9485544,0.005619955,0.0004277552,0.04321124,0.0002045319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02238368,0.000007102311,0.9691629,0.005873903,0.0002695612,0.0003758136,0.000001039767,0.000460827,0.001465208],"genre_scores_gemma":[0.9776542,5.67325e-7,0.02024984,0.001049204,0.00006441041,0.00005612312,0.000004576651,0.000009424512,0.0009116912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9552705,"threshold_uncertainty_score":0.4263493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04164809002946115,"score_gpt":0.2591887385175165,"score_spread":0.2175406484880553,"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."}}