{"id":"W6958031731","doi":"10.6068/dp157533ceaca58","title":"Trend 1991 - 2050. United States Census Bureau. Components of Population Change - International: Total Population | Country: Canada | Age Group: All Ages, 1991-2050. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-036-001.","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Population; Population statistics; Projections of population growth; Population growth; Demographic analysis; Demographic statistics; International comparisons","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":[0.001747843,0.00194429,0.002423972,0.005365069,0.00192856,0.00320734,0.003805716,0.001079831,0.06432742],"category_scores_gemma":[0.01105163,0.001329012,0.001793369,0.02207403,0.0004301643,0.002142472,0.001924728,0.003611376,0.04553188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0201333,"about_ca_system_score_gemma":0.0547663,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9556286,"about_ca_topic_score_gemma":0.9290755,"domain_scores_codex":[0.9979708,0.0001446572,0.0002528797,0.0002939202,0.0009290021,0.0004087556],"domain_scores_gemma":[0.9846028,0.0004900966,0.0004520623,0.000444017,0.01333709,0.0006740059],"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":[0.00002357119,0.000009143158,0.001155635,0.0003811075,0.00002858623,0.000006792007,0.00002301566,0.0001346197,0.00001286069,0.0003517145,0.995486,0.002386966],"study_design_scores_gemma":[0.0002099808,0.00001919791,0.03193571,0.001070461,0.00009463458,0.00003892428,0.0003878874,0.000532642,0.0001866095,0.0008125447,0.964643,0.00006839141],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006018113,0.00005264748,0.00003428887,0.00007018917,0.00003834476,0.00003105947,0.9989433,0.00005061074,0.0007194609],"genre_scores_gemma":[0.0007571636,0.0002665081,0.0003992177,0.0001097711,0.00001793198,0.0002252708,0.996519,0.000071503,0.001633636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06432742,"threshold_uncertainty_score":0.2151967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07349977988734709,"score_gpt":0.3329997823676403,"score_spread":0.2595000024802932,"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."}}