{"id":"W4414224825","doi":"10.64628/aam.vsp5ugawr","title":"Canadian cities can prepare for climate change by building with nature","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Urban Green Space and Health","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Climate change; Government (linguistics); Global warming; Work (physics)","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":[0.0005812941,0.0008408601,0.0003975857,0.001001565,0.003152173,0.003886311,0.0006777534,0.001777979,0.07035972],"category_scores_gemma":[0.00271873,0.000277695,0.0007277871,0.002669184,0.0008404084,0.00134315,0.001179622,0.00128735,0.005351775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01807514,"about_ca_system_score_gemma":0.02419779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9577895,"about_ca_topic_score_gemma":0.9803376,"domain_scores_codex":[0.9995639,0.00003315139,0.000006229935,0.00004051518,0.0002579102,0.00009835977],"domain_scores_gemma":[0.999337,0.00007436526,0.00002113586,0.00007294527,0.0003546293,0.000139971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005479156,0.00003201235,0.0024008,0.0001014217,0.00005166258,0.0001420632,0.0005401448,0.004948802,0.0005041932,0.282734,0.6676874,0.04080273],"study_design_scores_gemma":[0.00003079014,0.000004814896,0.006822599,0.00007827942,0.00003924427,0.00004881989,0.0009128083,0.00792005,0.001063826,0.08284185,0.9001973,0.00003970172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02596484,0.005225565,0.02368882,0.07088902,0.005052811,0.000109993,0.01844727,0.001252361,0.8493693],"genre_scores_gemma":[0.2857508,0.00536034,0.02779204,0.00382531,0.0008265132,0.00007629995,0.007525075,0.0009172302,0.6679264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07035972,"threshold_uncertainty_score":0.2353767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524553609044362,"score_gpt":0.2635318523119218,"score_spread":0.2482863162214781,"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."}}