{"id":"W2904867520","doi":"10.3390/su10124829","title":"Rethinking Performance Gaps: A Regenerative Sustainability Approach to Built Environment Performance Assessment","year":2018,"lang":"en","type":"article","venue":"Sustainability","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"University of Toronto","keywords":"Built environment; Sustainability; Occupancy; Cognitive reframing; Post-occupancy evaluation; Energy performance; Resilience (materials science); Computer science; Thermal comfort; Performance prediction; Architectural engineering; Performance indicator; Energy consumption; Environmental resource management; Engineering; Simulation; Civil engineering; Environmental science; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04838534,0.002290264,0.00146373,0.009798036,0.003582522,0.01320585,0.005067958,0.002979841,0.002920961],"category_scores_gemma":[0.07562762,0.0006086297,0.001262757,0.005109592,0.01302709,0.01897663,0.01461834,0.00593835,0.0004985126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01054688,"about_ca_system_score_gemma":0.01180604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008032036,"about_ca_topic_score_gemma":0.008263231,"domain_scores_codex":[0.9674593,0.01890558,0.001787418,0.002854978,0.007216467,0.001776375],"domain_scores_gemma":[0.9419332,0.03387902,0.006692143,0.005820229,0.01018764,0.00148791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001436067,0.0003780984,0.01912857,0.0009537269,0.0001619837,0.0002777006,0.02120075,0.0451923,0.00136737,0.7182799,0.003922793,0.1889931],"study_design_scores_gemma":[0.00001637054,0.0002895019,0.005700225,0.001069125,0.00006551818,0.0001394747,0.01891013,0.04825628,0.001479244,0.8975266,0.02639844,0.0001490792],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08870578,0.004374658,0.7684266,0.03884812,0.0006782481,0.0007883476,0.0005194995,0.0008148212,0.09684397],"genre_scores_gemma":[0.879989,0.001280489,0.1147339,0.001015737,0.0001804126,0.0005100132,0.0001740301,0.000138263,0.001978175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04838534,"threshold_uncertainty_score":0.2558892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401466602804132,"score_gpt":0.2592010056286587,"score_spread":0.2451863396006173,"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."}}