{"id":"W6901783351","doi":"10.6068/dp14ba7f94f6a37","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: 7 years, Females | 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":[0.002278853,0.002269252,0.002296604,0.007128327,0.00320469,0.004274172,0.004556758,0.00129398,0.1149433],"category_scores_gemma":[0.01638529,0.001622387,0.002081128,0.03166732,0.0006038449,0.002277795,0.002370926,0.003279061,0.05723055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05628449,"about_ca_system_score_gemma":0.1456862,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954927,"about_ca_topic_score_gemma":0.9935995,"domain_scores_codex":[0.9964579,0.0002735879,0.0003478497,0.0003791646,0.001751043,0.000790533],"domain_scores_gemma":[0.9731151,0.0007738593,0.0005414622,0.0006678503,0.0236273,0.001274375],"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":[0.00002206999,0.000006956318,0.0008990627,0.0002514968,0.00002209455,0.000007658163,0.00002919394,0.0001702089,0.00001099033,0.0005552086,0.9945068,0.003518239],"study_design_scores_gemma":[0.0001403562,0.00001353015,0.02043956,0.0008427339,0.00006660426,0.00003364349,0.0004587164,0.0006915841,0.0001561256,0.0009063316,0.976162,0.00008894015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009518439,0.0001288183,0.00009774075,0.0002547305,0.00007357153,0.0000477304,0.9962996,0.0001469952,0.002855713],"genre_scores_gemma":[0.002017833,0.0008705052,0.001496008,0.0003594788,0.00003981142,0.0003290691,0.9837011,0.0002913023,0.01089502],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1149433,"threshold_uncertainty_score":0.4083745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03322184527970327,"score_gpt":0.2714765311763644,"score_spread":0.2382546858966611,"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."}}