{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005791517,0.0003295811,0.0005839595,0.0007113034,0.0003612702,0.000431652,0.0007037466,0.0001109902,0.0000256824],"category_scores_gemma":[0.0001428931,0.0003566435,0.0002368818,0.001703215,0.0001209701,0.001096762,0.0004295161,0.0003462229,0.00005858278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001326044,"about_ca_system_score_gemma":0.00009814207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006849917,"about_ca_topic_score_gemma":0.0003503153,"domain_scores_codex":[0.9969213,0.0003840303,0.0006090677,0.000887313,0.0004508272,0.0007474722],"domain_scores_gemma":[0.9977645,0.0009167171,0.0004120351,0.0005499955,0.0002111447,0.0001456199],"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":[0.0001189903,0.0007029026,0.2229362,0.0001635344,0.0007928878,0.0003219749,0.02250163,0.005110412,0.03756321,0.00007568349,0.002575423,0.7071372],"study_design_scores_gemma":[0.001820569,0.0002082795,0.03834722,0.0001438081,0.00006492381,0.00002613436,0.0009289322,0.9142894,0.04266263,0.0000127232,0.0008301568,0.0006651822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4841922,0.00002267118,0.5144896,0.0001973608,0.0003959929,0.0002834293,0.000008005779,0.000192686,0.0002180437],"genre_scores_gemma":[0.9896864,0.000001256394,0.009149877,0.0008137481,0.0001994912,0.00002432997,0.000009971597,0.00002511511,0.0000898352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.909179,"threshold_uncertainty_score":0.9998885,"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."}}