{"id":"W6939456780","doi":"10.6084/m9.figshare.1425509","title":"Learning from failure: understanding the anticipated–achieved building energy performance gap","year":2015,"lang":"en","type":"article","venue":"Figshare","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Key (lock); Sustainability; Energy performance; Building science; Efficient energy use; Building design","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02830664,0.0008858058,0.001099549,0.005068752,0.003803753,0.01419548,0.003786378,0.003914171,0.004282243],"category_scores_gemma":[0.06507919,0.0004309767,0.0006063952,0.003242939,0.01885674,0.02979753,0.01457265,0.007233493,0.0006672534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01005156,"about_ca_system_score_gemma":0.005488749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003895568,"about_ca_topic_score_gemma":0.003571444,"domain_scores_codex":[0.9838561,0.00717284,0.0007590301,0.001275691,0.004338255,0.002598063],"domain_scores_gemma":[0.9368005,0.04398138,0.006970771,0.002330909,0.007210322,0.002706146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005252704,0.0007785933,0.08197569,0.001862117,0.0001130663,0.001907811,0.2723202,0.01847697,0.00113859,0.3818869,0.009519019,0.2294959],"study_design_scores_gemma":[0.00003802036,0.0007788824,0.04726369,0.001720552,0.00004405714,0.0007540581,0.3573347,0.01733017,0.001706746,0.523558,0.0492516,0.0002194548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7304342,0.006157184,0.07470511,0.0619934,0.0004231225,0.0002175997,0.000398582,0.0003471017,0.1253237],"genre_scores_gemma":[0.9940315,0.0008337647,0.003346704,0.0006505277,0.00004738006,0.00007098698,0.00007468659,0.00005342402,0.0008910006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02830664,"threshold_uncertainty_score":0.1497017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08492339810872405,"score_gpt":0.2200041644448422,"score_spread":0.1350807663361182,"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."}}