{"id":"W2374768355","doi":"","title":"INTRODUCE AND DISCUSS ON A GUIDE TO GREEN INFRASTRUCTURE FOR CANADIAN MUNICIPALITIES","year":2005,"lang":"en","type":"article","venue":"Chengshi guihua huikan","topic":"Environmental Quality and Pollution","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Green infrastructure; Connotation; Critical infrastructure; Modernization theory; Sustainable development; Business; Urban infrastructure; Environmental planning; Environmental resource management; Geography; Ecology; Engineering; Urban planning; Civil engineering; Computer science; Economic growth; Economics; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002707894,0.0001722304,0.0001404535,0.00005020179,0.0002677435,0.00003532543,0.0002281592,0.00009269762,0.001092902],"category_scores_gemma":[0.00008795398,0.0001533909,0.00004140076,0.00009367071,0.000151853,0.0001709253,0.0001155073,0.0001205408,0.0002766694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005420962,"about_ca_system_score_gemma":0.00001422102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05816479,"about_ca_topic_score_gemma":0.2611571,"domain_scores_codex":[0.9988555,0.00004078147,0.0001964532,0.0003559741,0.0001498891,0.0004014078],"domain_scores_gemma":[0.9992039,0.00005125882,0.00003723377,0.0003211369,0.00000277405,0.0003836697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002908189,0.0001892119,0.05054556,0.0001329468,0.000101111,0.0000066097,0.04943611,0.01142612,0.01441348,0.01497598,0.4500102,0.4084719],"study_design_scores_gemma":[0.0002905793,0.0001126508,0.0808512,0.00001524606,0.00001226077,0.000003790234,0.0006766345,0.0002202378,0.001862648,0.0006117243,0.9150978,0.000245202],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572423,0.00004159836,0.0001068618,0.02296262,0.0001266991,0.0005826975,0.0002342335,0.0000402777,0.01866268],"genre_scores_gemma":[0.9785329,0.00001219452,0.003870134,0.008289937,0.0003542012,0.00005838928,0.00004384844,0.00002306116,0.008815373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4650877,"threshold_uncertainty_score":0.9998202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01002822494048907,"score_gpt":0.2540707242309184,"score_spread":0.2440424992904293,"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."}}