{"id":"W2746292516","doi":"10.17645/up.v2i3.1026","title":"Trying to Smart-In-Up and Cleanup Our Act by Linking Regional Growth Planning, Brownfields Remediation, and Urban Infill in Southern Ontario Cities","year":2017,"lang":"en","type":"article","venue":"Urban Planning","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Redevelopment; Brownfield; Environmental planning; Infill; Metropolitan area; Urban sprawl; Government (linguistics); Urban planning; Sustainability; Retrofitting; Megacity; Real estate; Business; Local government; Geography; Civil engineering; Engineering; Political science; Public administration; Economy; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0005677848,0.0001402073,0.0002026894,0.0001241432,0.001093631,0.0002648552,0.0001892065,0.0001653962,0.0000139972],"category_scores_gemma":[0.0001778992,0.0001560248,0.00001830447,0.00004422962,0.0001196787,0.0004054776,0.00009544533,0.0003469073,0.000004704095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001815161,"about_ca_system_score_gemma":0.000098666,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07803827,"about_ca_topic_score_gemma":0.1523072,"domain_scores_codex":[0.9986721,0.00006298951,0.0002524454,0.000282575,0.0002672257,0.0004626307],"domain_scores_gemma":[0.9994195,0.0001280846,0.0001443907,0.0001243557,0.00001407288,0.0001696619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002813035,0.000007171287,0.7430911,0.00004826754,0.000003450881,0.00001012675,0.25014,0.000007083808,0.00001250769,0.0002430657,0.006285402,0.0001236521],"study_design_scores_gemma":[0.0006017787,0.00005435053,0.7929128,0.0009122975,0.00001214721,0.000001848607,0.1912793,0.00002912704,0.00001075576,0.0002484007,0.01366311,0.0002740655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99201,0.001155563,0.00001352402,0.002118261,0.0002043594,0.0001833099,0.000008436728,0.00002284316,0.004283727],"genre_scores_gemma":[0.9947669,0.0001217066,0.0001139009,0.001144167,0.000266487,0.00001505678,0.00001669579,0.00001280349,0.003542312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07426895,"threshold_uncertainty_score":0.9281011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274196308255399,"score_gpt":0.3052746981720682,"score_spread":0.2625327350895142,"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."}}