{"id":"W6939645956","doi":"10.6068/dp14bace4969f67","title":"Trend 1991 - 2050. United States Census Bureau. Components of Population Change - International: Net Migration Rate | Country: Canada, 1991-2050. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-036-004.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Net migration rate; Population; Population statistics; Population growth; Demographic analysis; Emigration; Immigration","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":[0.001757684,0.001984369,0.002295243,0.005701586,0.001868122,0.003205544,0.004034512,0.001136575,0.06459558],"category_scores_gemma":[0.01176947,0.001298621,0.001748867,0.02398155,0.000456027,0.002171694,0.001879294,0.003626948,0.04886875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01778859,"about_ca_system_score_gemma":0.04529714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9463663,"about_ca_topic_score_gemma":0.914049,"domain_scores_codex":[0.9978313,0.0001504525,0.0002699934,0.000317049,0.0009931005,0.0004381034],"domain_scores_gemma":[0.9829022,0.0005749323,0.0005796156,0.000527758,0.01467277,0.0007428123],"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":[0.00002035231,0.00000839521,0.001087162,0.0003141803,0.0000224772,0.000005602969,0.00001903307,0.0001276833,0.00001162257,0.0002775484,0.9962903,0.001815645],"study_design_scores_gemma":[0.0002172431,0.00001952075,0.03393131,0.0009435756,0.00007633737,0.00003229117,0.0003804209,0.0005456686,0.0001862668,0.0007345463,0.9628623,0.00007052657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004651929,0.00003558899,0.00002525371,0.00005025188,0.00002782667,0.00001957787,0.9992848,0.00004389749,0.0004663365],"genre_scores_gemma":[0.0005431218,0.0001540193,0.0002739395,0.00006977524,0.00001368492,0.0001507405,0.9975969,0.00005919805,0.001138579],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06459558,"threshold_uncertainty_score":0.2160937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07044171334059525,"score_gpt":0.2871164638107968,"score_spread":0.2166747504702015,"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."}}