{"id":"W6945268228","doi":"10.25318/1010012901-fra","title":"Crédit hypothécaire à l'habitation, encours des principales catégories d'institutions prêteuses du secteur privé, Banque du Canada","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Economic and Business Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Limiting; Context (archaeology); Payment; Taxpayer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000382072,0.0008032086,0.001160553,0.0003202154,0.001272566,0.00028263,0.0006628582,0.0003214887,0.0006396114],"category_scores_gemma":[0.003612477,0.001054445,0.00008628277,0.0005010188,0.0005810713,0.000522852,0.0002039202,0.000438892,0.0001071431],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004895401,"about_ca_system_score_gemma":0.006129886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.664348,"about_ca_topic_score_gemma":0.9995746,"domain_scores_codex":[0.9961055,0.00006979216,0.001654403,0.001039199,0.00027541,0.0008556763],"domain_scores_gemma":[0.9953733,0.001177469,0.001622241,0.0006943824,0.0008897396,0.0002428536],"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":[0.0000145526,0.0001155552,0.03131697,0.001182395,0.000275632,0.00008930363,0.0003932405,0.001488262,8.523669e-7,0.05829499,0.9060095,0.0008187422],"study_design_scores_gemma":[0.0003386107,0.00005805105,0.09846011,0.0003516913,0.0001683993,0.00003382327,0.001110664,0.0007595345,0.00001251397,0.00155317,0.8960059,0.001147568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01425238,0.003459164,0.005709033,0.001869259,0.007377322,0.0007878305,0.9658324,0.00002377355,0.0006888016],"genre_scores_gemma":[0.04357628,0.005682306,0.001632702,0.0003072941,0.0007109224,0.0001921288,0.9456376,0.00008483384,0.002175965],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3352266,"threshold_uncertainty_score":0.9995044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02059824327598393,"score_gpt":0.2235206768128572,"score_spread":0.2029224335368733,"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."}}