{"id":"W7128867406","doi":"","title":"Les spécificités des espaces publics à l'échelle du territoire de Montréal. Cahier In.SITU 9","year":2023,"lang":"en","type":"other","venue":"Archipelago (Université du Québec à Montréal)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Publics; National library; Transformation (genetics)","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":[0.000408362,0.0004222524,0.0001819133,0.00187258,0.005248574,0.004735515,0.0008123419,0.0007612311,0.07246303],"category_scores_gemma":[0.001280757,0.0002636294,0.0002734939,0.003874694,0.002083014,0.001571619,0.002242212,0.000597088,0.004137788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01791087,"about_ca_system_score_gemma":0.01664606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9438011,"about_ca_topic_score_gemma":0.9817808,"domain_scores_codex":[0.9994561,0.00005054149,0.0000119985,0.00009021396,0.0002043036,0.0001867354],"domain_scores_gemma":[0.9993709,0.00006339411,0.00005777849,0.00004690787,0.0003032885,0.0001577117],"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":[0.0001377968,0.00007334081,0.09396067,0.001005257,0.00006535838,0.001816772,0.08305915,0.001898143,0.006005578,0.1882418,0.3300432,0.2936929],"study_design_scores_gemma":[0.000006571129,0.00001323571,0.08925703,0.0001676767,0.00002425691,0.0001742648,0.03118925,0.0002330433,0.0007285823,0.001404224,0.8767583,0.00004355219],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1557449,0.005346796,0.004302884,0.01419263,0.0004909527,0.0002265982,0.01699547,0.0006022172,0.8020976],"genre_scores_gemma":[0.4447945,0.002655247,0.003529159,0.000595691,0.00006638803,0.00009748279,0.004026012,0.0002807419,0.5439548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07246303,"threshold_uncertainty_score":0.242413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166539998035871,"score_gpt":0.1937038204865096,"score_spread":0.1820384205061509,"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."}}