{"id":"W6983023213","doi":"","title":"Le bois urbain du grand Montréal, un espace changeant et ambigu","year":2023,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Identity (music); Product (mathematics); Identification (biology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000640417,0.0003667704,0.0004516561,0.0003297897,0.0009419466,0.00005304701,0.0002534495,0.0003199139,0.0002825076],"category_scores_gemma":[0.0001633928,0.0004535623,0.0002613811,0.0009079213,0.00008809237,0.0003480855,0.0003040416,0.0002801053,0.0008843198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002097216,"about_ca_system_score_gemma":0.00009193088,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02889443,"about_ca_topic_score_gemma":0.1499204,"domain_scores_codex":[0.9979055,0.0002560141,0.0003278305,0.0004334653,0.0004183376,0.0006588301],"domain_scores_gemma":[0.9983842,0.0003158455,0.0003262261,0.0005305743,0.0001524471,0.0002907398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001661033,0.0002482656,0.001180198,0.0003025965,0.0002136979,0.001749983,0.007663166,0.002577548,0.0002437018,0.459176,0.5060858,0.02039289],"study_design_scores_gemma":[0.002133098,0.0001014251,0.006587551,0.0001784904,0.0002956645,0.0002682334,0.001686286,0.04954486,0.0001263312,0.01716013,0.921406,0.000511918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.467003,0.06256476,0.01049649,0.4491915,0.001432481,0.001105818,0.0004821668,0.0008867448,0.006837082],"genre_scores_gemma":[0.6048768,0.04012259,0.006218306,0.001117342,0.0006072341,0.00003197073,0.000653969,0.0002537065,0.3461181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4480741,"threshold_uncertainty_score":0.9998936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146724045030149,"score_gpt":0.2013815099541857,"score_spread":0.1867091054511708,"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."}}