{"id":"W2505822593","doi":"","title":"A Multiagent Approach to Personalization and Assistance to Multiple Persons in a Smart Home","year":2014,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Personalization; Key (lock); Computer science; Human–computer interaction; Home automation; Residence; Process (computing); Internet privacy; Computer security; World Wide Web; Telecommunications","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":[0.003449925,0.0001810193,0.0002393065,0.0002889819,0.000215251,0.0004001343,0.0007369156,0.0000723181,0.000006820473],"category_scores_gemma":[0.001408865,0.0002000686,0.00005882791,0.0008876655,0.00004893888,0.0003601436,0.000431487,0.0001424011,0.00005146762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001147123,"about_ca_system_score_gemma":0.00005927291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008440457,"about_ca_topic_score_gemma":0.003619812,"domain_scores_codex":[0.9958397,0.002497976,0.0002959387,0.0007230514,0.0003407978,0.0003025988],"domain_scores_gemma":[0.9970118,0.001012351,0.0001244914,0.0009725151,0.0006080681,0.0002707862],"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":[0.00005986578,0.002650177,0.1271365,0.0003987529,0.00007995981,0.000007202854,0.2200845,0.000191408,0.03043096,0.1408748,0.002811001,0.4752749],"study_design_scores_gemma":[0.00242915,0.000004159639,0.2150253,0.001384616,0.00001468921,0.00004716061,0.001083805,0.7197588,0.01179025,0.0005197675,0.04682583,0.001116437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1407245,0.00007381848,0.8452971,0.005089673,0.00007354622,0.0004604081,0.000008975942,0.0001409559,0.008131097],"genre_scores_gemma":[0.8967152,0.000006438172,0.1012463,0.000348731,0.000009413302,0.0001345271,0.00001694541,0.00001577323,0.001506686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7559907,"threshold_uncertainty_score":0.8158562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742510381062648,"score_gpt":0.2144331485454998,"score_spread":0.1970080447348733,"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."}}