{"id":"W3032505230","doi":"10.71781/2959","title":"Kirkland : généalogie d’une banlieue automobile","year":2019,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"French Urban and Social Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art","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":[0.0002788577,0.0002301477,0.0002346738,0.00189087,0.003375185,0.00232616,0.0006551953,0.0005189095,0.02211107],"category_scores_gemma":[0.001095906,0.0001960026,0.0002378252,0.003286163,0.001977895,0.001176902,0.001113576,0.0005526395,0.001961656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008671763,"about_ca_system_score_gemma":0.003880727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6916275,"about_ca_topic_score_gemma":0.8065288,"domain_scores_codex":[0.9996359,0.00007334935,0.0000094758,0.0001135554,0.00006862492,0.00009901364],"domain_scores_gemma":[0.9995247,0.0001226551,0.00006271469,0.00006103191,0.0001719793,0.00005701063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003148737,0.00005030218,0.1402417,0.0003276439,0.0001103682,0.003914063,0.05453211,0.009117131,0.005055356,0.5368236,0.02394596,0.2255668],"study_design_scores_gemma":[0.00001506615,0.00005480236,0.1449294,0.0004120467,0.00006588178,0.001619649,0.02210969,0.005093818,0.001181017,0.01874854,0.805641,0.0001290755],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5170726,0.005232784,0.02034234,0.002902523,0.0002238091,0.0001164943,0.006051722,0.0003281863,0.4477296],"genre_scores_gemma":[0.9084001,0.001582018,0.005949887,0.0001324525,0.00001471848,0.00004030696,0.001280238,0.00008193619,0.08251845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3083725,"threshold_uncertainty_score":0.6203771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107257999819705,"score_gpt":0.1904460521517255,"score_spread":0.1793734721535285,"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."}}