{"id":"W3150545993","doi":"10.1109/wsc48552.2020.9383937","title":"Cell-DEVS Models for CO<sub>2</sub> Sensors Locations in Closed Spaces","year":2020,"lang":"en","type":"article","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"DEVS; Occupancy; Energy consumption; Computer science; Latency (audio); Real-time computing; Formalism (music); Efficient energy use; Air conditioning; Global warming; Simulation; Modeling and simulation; Architectural engineering; Climate change; Engineering; Telecommunications; Ecology; Electrical engineering","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":[0.0008029213,0.0007333715,0.000722907,0.0006191597,0.0006711969,0.001844953,0.002154527,0.001728878,0.01170868],"category_scores_gemma":[0.003551461,0.0004107319,0.001126644,0.00102007,0.0009227009,0.001052837,0.0009984714,0.00149387,0.0009635547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257392,"about_ca_system_score_gemma":0.001507682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04094047,"about_ca_topic_score_gemma":0.03679156,"domain_scores_codex":[0.9995217,0.000132016,0.00002694926,0.00008188849,0.000113086,0.0001243373],"domain_scores_gemma":[0.9970951,0.001814204,0.0002034624,0.0001600346,0.0005410897,0.000186132],"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":[0.00003869361,0.00002134913,0.0007223777,0.00002728986,0.00001070169,0.0001109541,0.00008176554,0.9622904,0.0003499621,0.03412142,0.000688994,0.001536021],"study_design_scores_gemma":[0.000007726071,0.00001026232,0.00009473057,0.000004272956,0.000006133827,0.0000133086,0.00004123396,0.9947119,0.0001798209,0.003528741,0.001398039,0.000003913516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2519736,0.001000226,0.6547625,0.002452992,0.0005175313,0.0003607222,0.009238682,0.001406371,0.0782874],"genre_scores_gemma":[0.9059528,0.0006804002,0.05807284,0.0002943623,0.00006833456,0.0004875537,0.002431583,0.0001878784,0.03182419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04094047,"threshold_uncertainty_score":0.08140433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440202100884393,"score_gpt":0.197560666512867,"score_spread":0.1831586455040231,"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."}}