{"id":"W4387668851","doi":"10.1108/ijshe-12-2022-0409","title":"Fostering the use of sustainable design to reduce energy use and GHG emissions at Canadian universities: a life cycle cost analysis approach","year":2023,"lang":"en","type":"article","venue":"International Journal of Sustainability in Higher Education","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Payback period; Greenhouse gas; Sustainability; Environmental economics; Net present value; Context (archaeology); Life-cycle cost analysis; Investment (military); Efficient energy use; Sustainable development; Metropolitan area; Life-cycle assessment; Economics; Environmental resource management; Business; Engineering; Production (economics); Risk analysis (engineering)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008682333,0.0009580435,0.000507311,0.007074609,0.002577435,0.005513181,0.002048073,0.0008373919,0.003108436],"category_scores_gemma":[0.01618449,0.0005439296,0.001237235,0.006551485,0.001549988,0.002076114,0.001646916,0.001306917,0.000223212],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0963034,"about_ca_system_score_gemma":0.09193131,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8022235,"about_ca_topic_score_gemma":0.89636,"domain_scores_codex":[0.9912174,0.002386437,0.0002014684,0.0002428166,0.005014976,0.0009369886],"domain_scores_gemma":[0.9862153,0.00360114,0.0007545715,0.0004655184,0.00853632,0.0004271346],"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":[0.0002302893,0.0003714666,0.0482075,0.001620835,0.0004320048,0.0002346048,0.001862043,0.4240337,0.004929508,0.1211512,0.009749144,0.3871776],"study_design_scores_gemma":[0.00007450816,0.000893794,0.1363778,0.001657107,0.0008513211,0.0002619403,0.01160253,0.6505255,0.01123329,0.06023183,0.1256428,0.0006476472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4775508,0.008181683,0.2461949,0.01347677,0.0002132797,0.004128653,0.00372762,0.0004472045,0.2460791],"genre_scores_gemma":[0.8893052,0.003062662,0.09902366,0.0002848709,0.00002551749,0.00040678,0.0004876597,0.00006970895,0.007333952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9036966,"threshold_uncertainty_score":0.6987333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06061609871883585,"score_gpt":0.3050545342304872,"score_spread":0.2444384355116513,"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."}}