{"id":"W6939009987","doi":"10.6068/dp14ba7fd3c8197","title":"Trend 1971 - 2013. Statistics Canada. CANSIM: Population and Demography - Population Estimates and Projections | Country: Canada | Table: Estimates of population, by age group and sex for July 1 | Variable: 3 years, Both sexes | Units: # Persons, 1971-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-163.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Census; Population statistics; Economic statistics; Residence; Socioeconomic status; Projections of population growth; Demographic statistics","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":[0.002333878,0.002245006,0.002311963,0.007299353,0.003182916,0.00425307,0.004632776,0.001297092,0.1168804],"category_scores_gemma":[0.01733517,0.001629787,0.002065266,0.03269999,0.0006019303,0.002270886,0.002373148,0.003253747,0.05892108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05516084,"about_ca_system_score_gemma":0.1425582,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951758,"about_ca_topic_score_gemma":0.9932662,"domain_scores_codex":[0.9964083,0.0002802668,0.0003644077,0.0003886022,0.001775513,0.000782843],"domain_scores_gemma":[0.9721829,0.0008407247,0.0005751717,0.0007108673,0.0243922,0.00129823],"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":[0.00002132992,0.000006571886,0.0008395428,0.0002465374,0.0000208991,0.000007352362,0.00002760136,0.0001598398,0.0000104846,0.0005260804,0.9948226,0.003311229],"study_design_scores_gemma":[0.000147409,0.00001312552,0.01967392,0.0008553448,0.00006516192,0.00003251446,0.0004408755,0.0006755724,0.000153155,0.0009257465,0.9769287,0.00008856115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008459483,0.0001142836,0.0000943585,0.0002368727,0.00006802989,0.00004659152,0.9965514,0.0001425193,0.002661331],"genre_scores_gemma":[0.001802194,0.0007766364,0.001452283,0.0003412278,0.00003732801,0.0003237633,0.985276,0.0002836148,0.009706904],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1168804,"threshold_uncertainty_score":0.4002218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0250943351258513,"score_gpt":0.2627669059428016,"score_spread":0.2376725708169503,"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."}}