{"id":"W6944580309","doi":"10.25318/3410009701-fra","title":"Société canadienne d'hypothèques et de logement, logements mis en chantier, toutes les régions, désaisonnalisées au taux 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":"Economic shortage; Context (archaeology); Research methodology; West germany","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":[0.001523809,0.001778967,0.001431918,0.01018845,0.001346577,0.003831087,0.002256493,0.001336305,0.04975577],"category_scores_gemma":[0.01937373,0.0007831827,0.001562279,0.02174289,0.0007866881,0.001799757,0.001729194,0.002089354,0.03996812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008745264,"about_ca_system_score_gemma":0.02244355,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.721894,"about_ca_topic_score_gemma":0.8168227,"domain_scores_codex":[0.9980074,0.0002329283,0.0002605592,0.0004703322,0.0007069952,0.000321799],"domain_scores_gemma":[0.9896813,0.003036383,0.0006259512,0.001411428,0.004745364,0.000499578],"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":[0.00004006117,0.0000119744,0.004283075,0.0008874792,0.00005532059,0.00002145154,0.0000848446,0.0004056936,0.00005982398,0.001411343,0.9881715,0.004567321],"study_design_scores_gemma":[0.00005796953,0.000005805586,0.01513402,0.0005356568,0.0000417601,0.0000405006,0.0002870541,0.0003633462,0.0001738856,0.001057422,0.9822637,0.00003880745],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001972504,0.0001651459,0.00008049851,0.0001024911,0.00002323474,0.000007786058,0.9978671,0.0001635055,0.001392873],"genre_scores_gemma":[0.001365024,0.0003065644,0.0004797318,0.0000559935,0.0000120905,0.00006839301,0.9957839,0.00008107005,0.001847344],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.278106,"threshold_uncertainty_score":0.5594876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614868439613062,"score_gpt":0.3049129808366178,"score_spread":0.2887642964404872,"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."}}