{"id":"W6964064452","doi":"10.25318/3410014201-fra","title":"Société canadienne d'hypothèques et de logement, logements mis en chantier, toutes les régions rurales, pour Canada et les provinces, désaisonnalisées au taux annuel, trimestriel","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Mortgage and Housing Corporation","funders":"","keywords":"Context (archaeology); Economic shortage; Web site","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001339865,0.001382678,0.001250116,0.009589695,0.001304622,0.003303589,0.001796001,0.0008844775,0.03583848],"category_scores_gemma":[0.01814714,0.0006876686,0.001352636,0.02486787,0.0006811802,0.001426986,0.001412361,0.001628637,0.02034174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01176595,"about_ca_system_score_gemma":0.0312468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9029862,"about_ca_topic_score_gemma":0.9388351,"domain_scores_codex":[0.9981312,0.0001936388,0.0002504725,0.0003864443,0.000702059,0.0003362844],"domain_scores_gemma":[0.9893575,0.002511925,0.0008001126,0.001108925,0.005712277,0.000509216],"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":[0.00006820802,0.00001632062,0.0159156,0.001002783,0.0001063302,0.00002747223,0.0001570677,0.0005233265,0.00005863229,0.001628936,0.9739993,0.006496016],"study_design_scores_gemma":[0.00009798721,0.000009800511,0.07269318,0.0007247947,0.00009848045,0.00006048193,0.0006205401,0.0005239276,0.0002280125,0.0009673255,0.9239129,0.00006261273],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004356182,0.0001618564,0.00006163687,0.0001066819,0.00001794124,0.000009107102,0.9974159,0.0001053833,0.001685987],"genre_scores_gemma":[0.003418527,0.0003784033,0.0004429967,0.00006608713,0.00001365882,0.00008724764,0.9925028,0.00007033495,0.003019901],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09701383,"threshold_uncertainty_score":0.1951703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597092962319997,"score_gpt":0.2942931638661729,"score_spread":0.2783222342429729,"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."}}