{"id":"W2913198854","doi":"10.1016/j.buildenv.2019.01.055","title":"Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II","year":2019,"lang":"en","type":"article","venue":"Building and Environment","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":529,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Research Foundation Singapore","keywords":"Thermal comfort; ASHRAE 90.1; Thermal sensation; Air temperature; Statistics; Mean absolute error; Environmental science; Skin temperature; Simulation; Meteorology; Mathematics; Computer science; Mean squared error; Engineering; Geography","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":[0.0009237143,0.0005245141,0.0006048489,0.0005905699,0.0003430631,0.0008689679,0.001060378,0.0006108589,0.003545521],"category_scores_gemma":[0.002684698,0.0003038007,0.0007773001,0.0006449933,0.0001434514,0.0007917201,0.000368305,0.0005593043,0.001216706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006548152,"about_ca_system_score_gemma":0.0005797084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04577238,"about_ca_topic_score_gemma":0.03064007,"domain_scores_codex":[0.9994444,0.00008850887,0.00004953868,0.0001467739,0.000218353,0.00005234279],"domain_scores_gemma":[0.9988723,0.0003756945,0.00005198563,0.0002512716,0.0004235802,0.00002507729],"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":[0.0004731276,0.0001653917,0.03685025,0.0002040238,0.000185577,0.00008445756,0.00006980976,0.8884178,0.007861507,0.0008456488,0.008667379,0.05617493],"study_design_scores_gemma":[0.00002254649,0.00004109387,0.01247706,0.00001488899,0.00002945983,0.00002135302,0.00004451782,0.9785963,0.006337914,0.000165944,0.002230096,0.00001867434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8915738,0.001016238,0.06687108,0.0004202174,0.0002351812,0.00006837542,0.02153988,0.005473739,0.01280145],"genre_scores_gemma":[0.9762087,0.0001235034,0.01166894,0.00004684168,0.00001525958,0.00003019075,0.01046308,0.0003202361,0.001123346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04577238,"threshold_uncertainty_score":0.09101188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152865002176659,"score_gpt":0.2117387533476322,"score_spread":0.2002101033258656,"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."}}