{"id":"W7014944718","doi":"","title":"Regulatory and policy urban planning objectives revisited according to environmental indicators: The case of the greater Montreal","year":2019,"lang":"en","type":"other","venue":"Espace ÉTS (ETS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Urban planning; Government (linguistics); Work (physics); Public policy; Local government; Regional planning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004029002,0.0006394403,0.0006603216,0.001011915,0.0002073628,0.00008402621,0.0005759792,0.0003737879,0.0001759151],"category_scores_gemma":[0.000112238,0.0003963967,0.0001816462,0.0006135734,0.0004299553,0.00009860603,0.0006968964,0.0005012618,0.0005126055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003518205,"about_ca_system_score_gemma":0.00009473499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001485372,"about_ca_topic_score_gemma":0.0001689791,"domain_scores_codex":[0.9974754,0.000459054,0.0003112967,0.0007804639,0.0004263522,0.0005474234],"domain_scores_gemma":[0.9974843,0.0001314754,0.0007191493,0.001471824,0.000008121113,0.0001851314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004554493,0.0001458834,0.2449045,0.0003080973,0.001449642,0.000599731,0.04337887,0.0000789624,0.007791543,0.0006028473,0.6974097,0.002874674],"study_design_scores_gemma":[0.003826698,0.000344077,0.5335827,0.004793015,0.001127448,0.002317695,0.02710008,0.00008169014,0.003439192,0.00004842877,0.4204586,0.002880341],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8312283,0.003561403,0.000004349646,0.0004903261,0.0002226798,0.002952127,0.00151158,0.0002363606,0.1597929],"genre_scores_gemma":[0.8208745,0.00001640471,0.00003645452,0.0001601919,0.0005755835,0.00003649126,0.00001641275,0.0008999308,0.177384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2886782,"threshold_uncertainty_score":0.9998488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006795736454749507,"score_gpt":0.2420006820371073,"score_spread":0.2352049455823578,"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."}}