{"id":"W6976693622","doi":"10.6068/dp14ba7fdee3356","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 35 years, In-migrants, Both sexes | Units: # Persons, 1972-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-160.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Health and Medical Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Population; Population statistics; Demographic statistics; Summary statistics; Economic statistics; Socioeconomic status; Internal migration","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":[0.002087756,0.002241141,0.002528499,0.007169109,0.003102686,0.004503001,0.004884154,0.001242089,0.11376],"category_scores_gemma":[0.01695372,0.001561404,0.001862045,0.03597128,0.0006087323,0.002283399,0.00248715,0.002906653,0.05855746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04502463,"about_ca_system_score_gemma":0.1178757,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942452,"about_ca_topic_score_gemma":0.9920546,"domain_scores_codex":[0.996731,0.0002562412,0.0003763718,0.0004334371,0.001456471,0.0007464041],"domain_scores_gemma":[0.974226,0.0009140634,0.0006789408,0.0007957218,0.02197552,0.001409715],"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":[0.0000204259,0.000005556814,0.0009103442,0.0002258466,0.00001871478,0.000006861265,0.00002934141,0.0001141424,0.000008797403,0.0003646837,0.9961273,0.002168038],"study_design_scores_gemma":[0.000169783,0.00001267197,0.02256176,0.0009284404,0.00006144003,0.00003214412,0.0005404903,0.0005794425,0.0001559812,0.0008248216,0.9740432,0.00008977841],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005682553,0.00005483846,0.00004528168,0.0001334981,0.00003633575,0.00002332834,0.9983737,0.00008893388,0.001187195],"genre_scores_gemma":[0.001183379,0.0003772425,0.0007048692,0.0001996847,0.00002533415,0.0002171729,0.9917256,0.0001928634,0.00537394],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.11376,"threshold_uncertainty_score":0.380565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717204182282425,"score_gpt":0.2986948883926788,"score_spread":0.2715228465698545,"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."}}