{"id":"W3195614574","doi":"10.1016/j.scs.2021.103256","title":"Optimal control of high-rise building mechanical ventilation system for achieving low risk of COVID-19 transmission and ventilative cooling","year":2021,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Ventilation (architecture); Mechanical ventilation; Energy consumption; Transmission (telecommunications); Coronavirus disease 2019 (COVID-19); Environmental science; Automotive engineering; Simulation; Computer science; Engineering; Mechanical engineering; Medicine; Electrical engineering; Telecommunications; Anesthesia","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":[0.0006603574,0.000103347,0.0003814444,0.00003961129,0.0003085123,0.00002126442,0.00001751622,0.0001211528,0.00001156149],"category_scores_gemma":[0.0001986673,0.00009693125,0.0002026959,0.0001081734,0.00007354597,0.0001152513,0.00002057798,0.0001054434,2.09887e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001162385,"about_ca_system_score_gemma":0.0002003758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009990519,"about_ca_topic_score_gemma":6.754323e-7,"domain_scores_codex":[0.9990913,0.00007077574,0.0003237338,0.0001899342,0.000138746,0.0001855074],"domain_scores_gemma":[0.9989031,0.0002378111,0.0002257112,0.00007867006,0.0004560935,0.00009859759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02301905,0.001261629,0.06790139,0.1686621,0.005628095,0.0001416101,0.06250877,0.09286734,0.1467524,0.3988319,0.000721342,0.03170429],"study_design_scores_gemma":[0.02468621,0.001388012,0.02921319,0.00162024,0.002846575,0.00009183779,0.1789545,0.7054867,0.04917676,0.002421505,0.00360981,0.0005046561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4952871,0.0007711646,0.5034479,0.00007892683,0.00003908037,0.0003266141,0.00002235231,0.00001599853,0.00001087322],"genre_scores_gemma":[0.9959671,0.0002400664,0.003406469,0.00003387581,0.00007293799,0.00002270994,0.00002202905,0.00001199883,0.0002227781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6126193,"threshold_uncertainty_score":0.3952742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007520282124947578,"score_gpt":0.2581285786759007,"score_spread":0.2506082965509531,"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."}}