{"id":"W1990797434","doi":"10.3917/reru.052.0163","title":"Distances, interactions et analyse spatiale de la ville : le cas de montréal","year":2005,"lang":"fr","type":"article","venue":"Revue d’Économie Régionale & Urbaine","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Humanities; Physics; Geography; Art","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":[0.0003223532,0.000353151,0.0003348342,0.001933275,0.003594062,0.004501751,0.0008780892,0.0004292821,0.01138867],"category_scores_gemma":[0.001182877,0.0002308437,0.0002978272,0.004220286,0.003699624,0.001262338,0.001498542,0.000588134,0.0002726026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03286798,"about_ca_system_score_gemma":0.00923886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9776292,"about_ca_topic_score_gemma":0.9861963,"domain_scores_codex":[0.9994882,0.0001314067,0.000009698754,0.00009886391,0.0001116824,0.0001601873],"domain_scores_gemma":[0.9994924,0.0001706036,0.00007744623,0.00002420373,0.0001470862,0.00008834041],"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":[0.0002779885,0.00008804223,0.2247744,0.0004190417,0.0002252551,0.002954073,0.06653216,0.02780665,0.005318234,0.5802114,0.008571795,0.08282094],"study_design_scores_gemma":[0.00005169688,0.00008649584,0.673951,0.0002015476,0.000188175,0.000539678,0.08489998,0.02339484,0.001257608,0.02645775,0.1887495,0.0002216905],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8905958,0.002005189,0.004805086,0.001782465,0.00002443112,0.00005818281,0.00137405,0.00006210674,0.09929275],"genre_scores_gemma":[0.9893267,0.000297814,0.001063003,0.00003033354,0.000004621219,0.000013513,0.0001620586,0.000008792974,0.009093177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03286798,"threshold_uncertainty_score":0.238475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588627808636497,"score_gpt":0.2849000816457358,"score_spread":0.2690138035593709,"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."}}