{"id":"W4200410565","doi":"10.1108/ecam-02-2021-0133","title":"Creating space and time for innovation - a methodology for building adaptation design appraisal using physics-based simulation tools and interactive multi-objective optimization","year":2021,"lang":"en","type":"article","venue":"Engineering Construction & Architectural Management","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adaptation (eye); Building design; Systems engineering; Computer science; Decision support system; Management science; Engineering; Architectural engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001973465,0.0001854673,0.000180295,0.0002316405,0.0001447299,0.00009301178,0.00003003729,0.00006611306,0.000002102573],"category_scores_gemma":[0.0002503215,0.0002212995,0.00003336164,0.0003360901,0.00002377675,0.0002857377,0.00002363487,0.00008635484,4.030061e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009503417,"about_ca_system_score_gemma":0.00001289722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002616495,"about_ca_topic_score_gemma":3.420269e-7,"domain_scores_codex":[0.9992031,0.00004775234,0.0002399569,0.0002663202,0.00007088287,0.0001719656],"domain_scores_gemma":[0.9988729,0.0007926036,0.00008831595,0.00008033523,0.0001400428,0.00002578581],"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":[0.00005804518,0.000005930624,0.000007422684,0.000152093,0.0001022052,3.878956e-7,0.0002264668,0.9350838,0.0109613,0.005858644,4.504375e-7,0.04754326],"study_design_scores_gemma":[0.0008905313,0.00003862233,0.00006701861,0.00009696886,0.00008103516,0.00001042564,0.0001277752,0.9884137,0.009684122,0.0003480983,0.00002293381,0.0002187654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03393077,0.00004051108,0.9648812,0.00001929237,0.0002933658,0.0005923605,0.00001157581,0.0002226883,0.000008233741],"genre_scores_gemma":[0.3127703,0.000003082466,0.6869566,0.000007558912,0.00005926144,0.00009373398,0.00007499899,0.00002938516,0.000005073785],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2788395,"threshold_uncertainty_score":0.9024331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05284153874273201,"score_gpt":0.296629106780695,"score_spread":0.243787568037963,"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."}}