{"id":"W6907434257","doi":"10.25318/3610008201-fra","title":"Financement officiel net provenant des réserves officielles de liquidités internationales et des emprunts en devises étrangères du gouvernement du Canada, annuel","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cote d ivoire; New england; Public policy","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":[0.000536831,0.001343766,0.001151689,0.00736616,0.001144062,0.002604631,0.00174986,0.0008294671,0.02792003],"category_scores_gemma":[0.005194969,0.0005414305,0.0008016641,0.01744041,0.0004336749,0.0009943589,0.001053691,0.001475744,0.02158808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01179721,"about_ca_system_score_gemma":0.02068478,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9375824,"about_ca_topic_score_gemma":0.9604136,"domain_scores_codex":[0.9990239,0.00004935151,0.00008178216,0.0001887267,0.0004121191,0.0002441108],"domain_scores_gemma":[0.9963003,0.0003616799,0.0003013111,0.0002702419,0.002483459,0.0002831171],"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":[0.00004405861,0.00001124262,0.004189673,0.0003484459,0.00003093867,0.00002367305,0.00004638814,0.0003053037,0.00005550367,0.0007270142,0.9907897,0.003428016],"study_design_scores_gemma":[0.00009167412,0.000008472363,0.04516353,0.0003557298,0.00003776904,0.0000513636,0.0003052163,0.0006258155,0.0003565415,0.0004548482,0.9525087,0.0000403519],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002841474,0.00007564932,0.00002085177,0.00005128868,0.000008382394,0.000003913653,0.9987219,0.00005145197,0.0007824145],"genre_scores_gemma":[0.001243445,0.0001470536,0.0001251119,0.00002230797,0.000005429121,0.00001945818,0.996228,0.00002233705,0.002187009],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06241757,"threshold_uncertainty_score":0.1255702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0119129837162028,"score_gpt":0.2693736899932447,"score_spread":0.2574607062770419,"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."}}