{"id":"W6957773868","doi":"10.6068/dp14bad4118eb40","title":"Trend 1991 - 2050. United States Census Bureau. Components of Population Change - International: Fertility Rate for Age 45 - 49 | Country: Canada, 1991-2050. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-036-021.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Population; Population statistics; Fertility; Total fertility rate; Demographic analysis; Projections of population growth; Population growth; Population projection","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":[0.002076361,0.001916833,0.002361814,0.005129169,0.001750584,0.002892335,0.003937121,0.001120597,0.05878207],"category_scores_gemma":[0.01253603,0.001341447,0.001893452,0.02132666,0.0004311695,0.002029447,0.001862756,0.003574615,0.04186473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01828099,"about_ca_system_score_gemma":0.04616615,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9393421,"about_ca_topic_score_gemma":0.8998153,"domain_scores_codex":[0.9977398,0.0001827753,0.0003051604,0.0003200668,0.001020825,0.0004313111],"domain_scores_gemma":[0.9835293,0.0005904603,0.0005519101,0.0005159924,0.01410304,0.0007093827],"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":[0.00002789265,0.000009860704,0.001300356,0.0003749876,0.00002897454,0.000006621218,0.00002057579,0.0001421713,0.00001416052,0.0003123306,0.9954612,0.002300913],"study_design_scores_gemma":[0.0002794642,0.00002528405,0.04090877,0.001164343,0.0001053026,0.00004124901,0.0003640843,0.0005664175,0.0002116768,0.0008057897,0.9554506,0.0000769734],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005717527,0.00004716498,0.00003368567,0.00006562814,0.00003625609,0.00002941663,0.999145,0.00004941958,0.0005361362],"genre_scores_gemma":[0.000710326,0.0002226298,0.0003694255,0.0001019217,0.00001758769,0.0002166068,0.9971239,0.00006341629,0.001174244],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06065786,"threshold_uncertainty_score":0.1966456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096287911410893,"score_gpt":0.3268320813096535,"score_spread":0.2172032901685642,"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."}}