{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003506626,0.0005369781,0.0003021029,0.001779406,0.007273588,0.01132027,0.002650412,0.003488581,0.01615828],"category_scores_gemma":[0.006482966,0.0003873561,0.0005610783,0.00326481,0.005206186,0.002497802,0.003747843,0.003119844,0.0004298943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1204057,"about_ca_system_score_gemma":0.1207599,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9857284,"about_ca_topic_score_gemma":0.9937265,"domain_scores_codex":[0.9954722,0.0007230029,0.00007872113,0.0003854682,0.001405253,0.001935426],"domain_scores_gemma":[0.9974203,0.0004761725,0.00016889,0.0001191234,0.001089689,0.0007258555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007628756,0.00007351051,0.01497984,0.00016563,0.00007270342,0.001060327,0.00752675,0.006033975,0.001152416,0.8109456,0.122755,0.03515802],"study_design_scores_gemma":[0.0001245569,0.00009098685,0.1087881,0.0004023636,0.0001202451,0.0002169401,0.02508915,0.008282528,0.001157899,0.04039447,0.8150622,0.0002704478],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1906664,0.004784494,0.004064515,0.1566753,0.0004424537,0.0003620891,0.002815572,0.0002405268,0.6399487],"genre_scores_gemma":[0.770548,0.001275325,0.002981478,0.008370511,0.0001248563,0.0001253768,0.0004398418,0.0001404352,0.2159942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1204057,"threshold_uncertainty_score":0.8736089,"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."}}