{"id":"W2888789276","doi":"10.1016/j.neucom.2018.08.033","title":"Recognizing multi-resident activities in non-intrusive sensor-based smart homes by formal concept analysis","year":2018,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Formal concept analysis; Activity recognition; Home automation; Artificial intelligence; Telecommunications; Algorithm","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":[0.00129149,0.0003759043,0.0003198726,0.001133371,0.0003371609,0.001317232,0.0007096603,0.000433176,0.0007648359],"category_scores_gemma":[0.00359611,0.0002006643,0.0009412644,0.0006247772,0.001170548,0.002320802,0.0007027478,0.000552171,0.0001344071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000851263,"about_ca_system_score_gemma":0.001170444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005467576,"about_ca_topic_score_gemma":0.005673345,"domain_scores_codex":[0.9989929,0.000283263,0.00008793004,0.0002414669,0.0003000846,0.00009443689],"domain_scores_gemma":[0.9981186,0.001097934,0.000300667,0.0001388136,0.0002910506,0.00005298722],"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":[0.0004399553,0.000524683,0.02841179,0.0005602562,0.0002483769,0.001327629,0.003419474,0.4133853,0.03965225,0.2355741,0.00188069,0.2745754],"study_design_scores_gemma":[0.00001110625,0.00005299048,0.00218153,0.00004116227,0.00004413676,0.0001681429,0.0003488699,0.9441119,0.004125795,0.04794041,0.0009561913,0.0000177598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07412496,0.0002138009,0.9241618,0.0001145058,0.00001985067,0.00006669811,0.0001325611,0.0003046813,0.0008612166],"genre_scores_gemma":[0.8055882,0.000171501,0.193271,0.00003697658,0.00002121536,0.0001085376,0.0002185797,0.0000259119,0.0005580425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005467576,"threshold_uncertainty_score":0.01087147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02129577417734746,"score_gpt":0.2688916674304313,"score_spread":0.2475958932530838,"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."}}