{"id":"W6938924027","doi":"10.6068/dp14ba7ee8fff5","title":"Trend 1971 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Number of non-permanent residents, by age group and sex for July 1 | Variable: 24 years, Males | Units: # Persons, 1971-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-160.","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; Official statistics; Population statistics; Summary statistics; Demographic statistics; Socioeconomic status; Economic 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":[0.002027795,0.002224309,0.002540177,0.007113496,0.003055649,0.004365668,0.004926017,0.001226856,0.1098307],"category_scores_gemma":[0.01678657,0.001528334,0.001861766,0.03488426,0.0006026829,0.00228096,0.002391527,0.002956422,0.05929434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04487793,"about_ca_system_score_gemma":0.1166194,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942169,"about_ca_topic_score_gemma":0.9920641,"domain_scores_codex":[0.9968197,0.0002434375,0.0003585145,0.0004141847,0.001434746,0.000729389],"domain_scores_gemma":[0.9737841,0.0009003346,0.0006623429,0.00075547,0.02254299,0.001354719],"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":[0.0000194993,0.000005802037,0.0009507806,0.0002225804,0.00001844047,0.000006725053,0.00002787215,0.0001203351,0.000008376825,0.0003561404,0.9960473,0.002216176],"study_design_scores_gemma":[0.000167496,0.00001310673,0.02399364,0.0009214976,0.0000614666,0.0000328438,0.0005254662,0.0006232276,0.0001565746,0.0008132032,0.9726011,0.00009034955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006230074,0.00005817228,0.00004543307,0.000140281,0.00003768194,0.00002396551,0.9983338,0.00008980089,0.001208699],"genre_scores_gemma":[0.001237071,0.0004068137,0.0006807074,0.0001981378,0.00002623781,0.0002126312,0.9916546,0.0001886091,0.005395071],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1098307,"threshold_uncertainty_score":0.3674204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02205212848385359,"score_gpt":0.2590069679206695,"score_spread":0.2369548394368159,"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."}}