{"id":"W2066238811","doi":"10.1109/mprv.2012.58","title":"A Smarter Smart Home: Case Studies of Ambient Intelligence","year":2012,"lang":"en","type":"article","venue":"IEEE Pervasive Computing","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"British Columbia Institute of Technology","keywords":"Ambient intelligence; Ubiquitous computing; Computer science; Home automation; Smart environment; Human–computer interaction; Psychological intervention; Internet of Things; Risk analysis (engineering); Computer security; Telecommunications; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006486854,0.000215677,0.0003257364,0.0003125252,0.0002501076,0.00003898395,0.0005651036,0.00008451251,0.00000825751],"category_scores_gemma":[0.0002015294,0.0002026435,0.00009326057,0.0006709461,0.0002433985,0.0006414345,0.0004558212,0.0003284979,0.0001039727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000143889,"about_ca_system_score_gemma":0.0000299871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002694234,"about_ca_topic_score_gemma":0.00001077768,"domain_scores_codex":[0.9982802,0.0001167463,0.0005229121,0.000363612,0.0002246748,0.0004919062],"domain_scores_gemma":[0.9979289,0.0003858119,0.0003575527,0.000534447,0.0007368876,0.00005642026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006296663,0.001853099,0.10513,0.0007952066,0.001690942,0.00319976,0.173499,0.001437545,0.1092599,0.2385665,0.007725985,0.3567792],"study_design_scores_gemma":[0.0008123847,0.0009563159,0.01171789,0.0008269266,0.00009861965,0.01804385,0.01435676,0.08151131,0.8613662,0.00688743,0.001701421,0.001720914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6542412,0.0002616282,0.3426057,0.0001788677,0.002277938,0.0001304154,9.683414e-7,0.0001345205,0.0001687534],"genre_scores_gemma":[0.9790968,0.000009232888,0.02036207,0.0002838636,0.0001862075,0.000009283616,6.081792e-7,0.0000121456,0.00003983278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7521063,"threshold_uncertainty_score":0.8263561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0776350492863366,"score_gpt":0.3513019000280085,"score_spread":0.2736668507416719,"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."}}