{"id":"W4319317009","doi":"10.3390/su15042884","title":"Novel Neural Network Optimized by Electrostatic Discharge Algorithm for Modification of Buildings Energy Performance","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Artificial neural network; Computer science; Algorithm; Energy (signal processing); Computation; Feedforward neural network; Data mining; Artificial intelligence; Machine learning; Mathematics; Statistics","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":[0.0003856645,0.0007394581,0.0005175928,0.0003866544,0.0002655668,0.0005282349,0.0007917496,0.0006873515,0.00129059],"category_scores_gemma":[0.0008230657,0.0002711407,0.0005508302,0.0004183376,0.0002141067,0.0005733944,0.0003993321,0.0005723021,0.0002167969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005863492,"about_ca_system_score_gemma":0.0007066217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007660537,"about_ca_topic_score_gemma":0.006018892,"domain_scores_codex":[0.9998487,0.00002636664,0.00001068191,0.0000420469,0.00004681809,0.00002532658],"domain_scores_gemma":[0.999843,0.00005583846,0.00001892499,0.000008817614,0.00006697613,0.000006392476],"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":[0.00004505,0.00003849155,0.000813815,0.00004050645,0.00003137071,0.00003378601,0.00002491597,0.9208626,0.002399993,0.0014328,0.0006424976,0.0736341],"study_design_scores_gemma":[0.000002299417,0.00001186978,0.00008364414,0.00000180585,0.000003494188,0.000003740282,0.000001699579,0.99926,0.0003586803,0.0001444467,0.0001265845,0.000001603195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06779761,0.0006736605,0.923744,0.0001790736,0.00009126651,0.00006946196,0.00005540188,0.0008049883,0.006584569],"genre_scores_gemma":[0.8713705,0.0004206262,0.1214837,0.0001287593,0.00003761574,0.0002329014,0.0002049906,0.00006727625,0.006053544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007660537,"threshold_uncertainty_score":0.01523191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006729217275355961,"score_gpt":0.2230350923186397,"score_spread":0.2163058750432837,"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."}}