{"id":"W4285464380","doi":"10.32920/ryerson.14661111.v1","title":"Ontario's public infrastructure : adapting to climate change","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Sustainable Building Design and Assessment","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pace; Adaptation (eye); Portfolio; Climate change; Face (sociological concept); Climate change adaptation; Process management; Environmental resource management; Business; Environmental planning; Risk analysis (engineering); Finance; Economics; Geography; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001927682,0.0003876032,0.0003831426,0.000227948,0.0000698861,0.0005369223,0.0003429873,0.000303245,0.002015963],"category_scores_gemma":[0.0000217926,0.0004026744,0.0001227058,0.0001980028,0.000007282775,0.0001464331,0.0009539202,0.0008386974,0.00002010017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008477492,"about_ca_system_score_gemma":0.0002420262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002654895,"about_ca_topic_score_gemma":0.007721985,"domain_scores_codex":[0.9983088,0.00002590114,0.0002872854,0.0004416457,0.0002525602,0.0006837546],"domain_scores_gemma":[0.9990557,0.00002336767,0.00003894751,0.0005362965,0.0001151941,0.0002305018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002603876,0.0001586409,0.03255651,0.006498007,0.001243416,0.0008692264,0.02676004,0.4080215,0.00229134,0.01785063,0.04428517,0.4594394],"study_design_scores_gemma":[0.00152901,0.0002149474,0.09035906,0.003632875,0.0003619036,0.0001095662,0.0244553,0.1280109,0.00244166,0.004470348,0.7361579,0.008256488],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7047104,0.001416188,0.1450531,0.00167144,0.007470537,0.002554208,0.00003924019,0.003292801,0.1337921],"genre_scores_gemma":[0.9607285,0.00009205092,0.03707405,0.0004357054,0.0004537395,0.0003334946,0.00008310856,0.00008736197,0.0007119868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6918727,"threshold_uncertainty_score":0.9998425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04049914317525601,"score_gpt":0.2461673242454499,"score_spread":0.2056681810701939,"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."}}