{"id":"W6982874015","doi":"","title":"L’analyse multicritère pour une planification multidisciplinaire : Le cas des rues conviviales à Québec","year":2019,"lang":"fr","type":"other","venue":"Espace ÉTS (ETS)","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Set (abstract data type); Table (database); Subject (documents)","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":[0.003840903,0.0008555716,0.0006173868,0.002423408,0.005669505,0.005703492,0.001384323,0.002109149,0.009205598],"category_scores_gemma":[0.008300986,0.0003745654,0.001182029,0.003743378,0.001497987,0.001928264,0.002302891,0.002338827,0.0003891313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0341913,"about_ca_system_score_gemma":0.03918912,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9493837,"about_ca_topic_score_gemma":0.9720987,"domain_scores_codex":[0.9968136,0.001167006,0.0001298273,0.0003663602,0.0008178941,0.0007052968],"domain_scores_gemma":[0.994695,0.002383731,0.0004154895,0.0002819067,0.001676378,0.0005475598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004769833,0.0008700294,0.36996,0.0005603315,0.0008299345,0.007693313,0.0425348,0.03506509,0.002365771,0.1351883,0.03098636,0.3734691],"study_design_scores_gemma":[0.0001211589,0.0002924154,0.5659792,0.001537683,0.0003379694,0.001803467,0.1147279,0.08162021,0.001755747,0.01840913,0.2131737,0.000241313],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8763671,0.007902138,0.02581495,0.02843211,0.0002823702,0.0002862616,0.002370523,0.00017176,0.0583727],"genre_scores_gemma":[0.9560317,0.00203032,0.01481176,0.0005509594,0.00007678333,0.0001577147,0.0006139351,0.0000732594,0.02565356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05061632,"threshold_uncertainty_score":0.2480764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04016520038579684,"score_gpt":0.310415362264968,"score_spread":0.2702501618791712,"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."}}