{"id":"W2070885583","doi":"10.1109/cica.2014.7013250","title":"Ensuring safe prevention and reaction in smart home systems dedicated to people becoming disabled","year":2014,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Home automation; Controller (irrigation); Risk analysis (engineering); Control (management); Formal verification; Computer security; Human–computer interaction; Embedded system; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006573084,0.0004636359,0.0003331603,0.0003336759,0.0005438202,0.0006690552,0.0004878304,0.0005363753,0.001202509],"category_scores_gemma":[0.002478244,0.0002331578,0.0003632708,0.00009960856,0.0009226091,0.0007714616,0.0009900857,0.0004566915,0.0002778786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004258308,"about_ca_system_score_gemma":0.0009100417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001867171,"about_ca_topic_score_gemma":0.002097571,"domain_scores_codex":[0.9993297,0.0002010656,0.00005565205,0.0001430511,0.0001810981,0.00008953628],"domain_scores_gemma":[0.9991053,0.0004473429,0.0001610512,0.0001278992,0.0001188604,0.00003951004],"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":[0.001156307,0.0004380237,0.009227651,0.0008120599,0.0001034149,0.001921599,0.003836704,0.3539252,0.2378104,0.0942553,0.001427406,0.295086],"study_design_scores_gemma":[0.0001965505,0.0006385263,0.003233261,0.0001506582,0.0001426997,0.0006392032,0.0007315172,0.774012,0.1508362,0.06074584,0.008589108,0.00008438002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1342632,0.0001495387,0.8599479,0.0001498993,0.00002915271,0.0001450112,0.00005076852,0.001345544,0.003919085],"genre_scores_gemma":[0.9442013,0.0001237303,0.05416455,0.00004383186,0.000007728944,0.0001191628,0.00004048445,0.00004226355,0.001256937],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001867171,"threshold_uncertainty_score":0.004022837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256739724758282,"score_gpt":0.2518773799076067,"score_spread":0.2293099826600239,"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."}}