{"id":"W4253918905","doi":"10.1002/9783433604663.ch5","title":"Monitoring and post‐occupancy evalution of Net<scp>ZEBs</scp>","year":2017,"lang":"en","type":"other","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Occupancy; Thermal comfort; Architectural engineering; Post-occupancy evaluation; Indoor air quality; Energy performance; Engineering; Continuous monitoring; Computer monitoring; Transport engineering; Computer science; Efficient energy use; Real-time computing; Operations management; Environmental engineering; Meteorology","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":[0.0006236394,0.0003631391,0.00024878,0.000799197,0.0003460259,0.0005376111,0.0005717986,0.0001869431,0.01268752],"category_scores_gemma":[0.001346687,0.0001944657,0.0001356793,0.000661299,0.0001808461,0.0003360446,0.0005843716,0.0002752597,0.002427442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005784346,"about_ca_system_score_gemma":0.0004647477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01001907,"about_ca_topic_score_gemma":0.02463916,"domain_scores_codex":[0.99933,0.00008594246,0.00002202429,0.00007165773,0.0004375517,0.00005279132],"domain_scores_gemma":[0.9988626,0.0001764536,0.00013779,0.0001684068,0.0005547317,0.0001000201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00319988,0.0004900142,0.2458367,0.0005152646,0.00007431584,0.0004929662,0.001894607,0.04170464,0.117799,0.002162904,0.0299404,0.5558892],"study_design_scores_gemma":[0.00004273093,0.001380904,0.7447938,0.00007471584,0.00004453796,0.0002508664,0.001913701,0.08580979,0.1135449,0.00073074,0.05132998,0.00008334583],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8953432,0.000101634,0.04434788,0.0001107885,0.00005501402,0.0004489007,0.008096372,0.002620699,0.04887549],"genre_scores_gemma":[0.9567339,0.00007966397,0.01646737,0.00002060934,0.00001095489,0.0002489595,0.004851823,0.0004042097,0.02118257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01268752,"threshold_uncertainty_score":0.04244405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008631776893813198,"score_gpt":0.2233582956917658,"score_spread":0.2147265187979526,"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."}}