{"id":"W4416812652","doi":"10.1016/j.buildenv.2025.114073","title":"Occupant-centric demand-controlled ventilation strategy for airport terminals using Wi-Fi data and CFD simulations","year":2025,"lang":"en","type":"article","venue":"Building and Environment","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Setpoint; ASHRAE 90.1; Thermal comfort; Ventilation (architecture); Computational fluid dynamics; Thermostat; Energy consumption; Energy recovery ventilation","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":[0.0003023682,0.0001109276,0.0002513811,0.0001257287,0.0002298987,0.00003771437,0.00003175027,0.00006639561,0.00002511028],"category_scores_gemma":[0.00004982744,0.00009937905,0.00004154102,0.00005326135,0.00003018543,0.0001212338,0.00005139202,0.00005572746,7.223785e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004840729,"about_ca_system_score_gemma":0.00002789238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218467,"about_ca_topic_score_gemma":0.000001520563,"domain_scores_codex":[0.9991758,0.00002189834,0.0002711881,0.0002899694,0.0000966712,0.0001444112],"domain_scores_gemma":[0.9995397,0.00008637139,0.0001005738,0.0002076801,0.00001355346,0.00005216776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004448926,0.0008745348,0.6296951,0.0007488271,0.001008989,0.00001728947,0.0002137825,0.1038127,0.06130406,0.001793679,0.0007959944,0.1952862],"study_design_scores_gemma":[0.006963597,0.0001020632,0.1607693,0.0001148124,0.0008089938,0.00001729741,0.00003115748,0.8238302,0.0004332464,0.0003903768,0.006417543,0.000121387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7352608,0.0007947653,0.2628043,0.0001740029,0.00009439498,0.0007510376,0.00003094311,0.00002012,0.00006964184],"genre_scores_gemma":[0.9972139,0.0001504954,0.001962523,0.00008005396,0.00009857069,0.00001734853,0.0001139687,0.000008216813,0.0003549194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7200176,"threshold_uncertainty_score":0.405256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0532489885485052,"score_gpt":0.3415105971346087,"score_spread":0.2882616085861035,"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."}}