{"id":"W4319967909","doi":"10.1016/j.enbuild.2023.112851","title":"Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings","year":2023,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":182,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Dashboard; Retrofitting; Computer science; Engineering; Systems engineering; Data science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007945799,0.000160204,0.0001801161,0.0001142941,0.00008456864,0.00009103561,0.00009622385,0.00008335028,0.000004735667],"category_scores_gemma":[0.00004210961,0.0001516639,0.00004051784,0.0002382711,0.0000503175,0.0005352982,0.00003510337,0.0001291857,0.000001001375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000298541,"about_ca_system_score_gemma":0.000007641595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002152166,"about_ca_topic_score_gemma":6.497466e-7,"domain_scores_codex":[0.9991971,0.000004156952,0.0002292019,0.0001676992,0.0001634414,0.0002384605],"domain_scores_gemma":[0.9995576,0.0002012898,0.00005403535,0.00007308578,0.00004432378,0.00006967569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002710776,0.00004935148,0.07381074,0.0005422254,0.0005687516,0.00001671059,0.00316456,0.7623375,0.01959831,0.006858652,0.0005649128,0.1322172],"study_design_scores_gemma":[0.005018413,0.001166631,0.007572207,0.002830498,0.0002012464,0.00003828021,0.006463746,0.3268687,0.4765651,0.00426219,0.167029,0.001984062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9441849,0.0001872846,0.04725258,0.00001989044,0.0001977369,0.00007981252,0.000127634,0.0005242533,0.007425892],"genre_scores_gemma":[0.9976866,0.00006432351,0.001485967,0.000003213995,0.0001482993,0.00003384822,0.00008099117,0.00004357045,0.0004532298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4569668,"threshold_uncertainty_score":0.6184674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01999692105007831,"score_gpt":0.2300050647487981,"score_spread":0.2100081436987198,"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."}}