{"id":"W4244323840","doi":"10.32920/ryerson.14646207.v1","title":"Growing with the Flow: Planning for Smart Growth in Ontario Through Water & Wastewater Infrastructure Service Provision","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Smart growth; Growth management; Sustainability; Business; Legislation; Urban sprawl; Water supply; Sustainable growth rate; Environmental planning; Service (business); Infill; Natural resource economics; Environmental resource management; Environmental economics; Urban planning; Environmental science; Economics; Finance; Engineering; Environmental engineering; Civil engineering; Ecology; Marketing","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":[0.0007575633,0.0001536069,0.0001285046,0.0006139907,0.008804943,0.003141481,0.0007028798,0.0006737351,0.004678606],"category_scores_gemma":[0.001834339,0.0002258617,0.000218048,0.001506625,0.002967037,0.001253848,0.001589481,0.0007634633,0.0002860274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1077643,"about_ca_system_score_gemma":0.1801848,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.988381,"about_ca_topic_score_gemma":0.9972511,"domain_scores_codex":[0.9990207,0.0001524272,0.00001875637,0.00006415095,0.0002389426,0.0005051738],"domain_scores_gemma":[0.9983796,0.0002363868,0.0001807197,0.00004971632,0.0004354284,0.0007181891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000236541,0.0002288563,0.1971045,0.0006413073,0.00006162909,0.00400243,0.1004732,0.01394549,0.005303308,0.3727805,0.1394131,0.1658092],"study_design_scores_gemma":[0.0000435228,0.0001155832,0.2467545,0.0002607532,0.00004622395,0.0002437956,0.1391767,0.009254885,0.001702228,0.02814344,0.5741484,0.0001100407],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6914371,0.001200568,0.004787193,0.05717219,0.00007636601,0.0003416933,0.001490298,0.0001160816,0.2433786],"genre_scores_gemma":[0.9474427,0.001279832,0.003368773,0.0007795496,0.00001455844,0.0000604074,0.0002652464,0.0000273496,0.04676166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1077643,"threshold_uncertainty_score":0.7818887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02616850284130448,"score_gpt":0.2702760139843219,"score_spread":0.2441075111430174,"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."}}