{"id":"W6938935104","doi":"10.6068/dp14ba7f920fb20","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 85 years, Net-migration, Males | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Population; Population statistics; Summary statistics; Demographic 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":[0.002049505,0.002290997,0.002548125,0.007319216,0.003088011,0.004506082,0.004970829,0.001249254,0.1122882],"category_scores_gemma":[0.01611721,0.001564536,0.00190057,0.03604184,0.0006085284,0.002289231,0.002438674,0.002971103,0.05853386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04571196,"about_ca_system_score_gemma":0.1187436,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943898,"about_ca_topic_score_gemma":0.9920548,"domain_scores_codex":[0.9967287,0.0002507204,0.0003725548,0.0004331107,0.001470161,0.0007449107],"domain_scores_gemma":[0.9744518,0.0008767848,0.0006775734,0.0007625794,0.02182219,0.001409123],"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":[0.000020401,0.000005775209,0.0009381271,0.0002264298,0.00001925435,0.000006891641,0.0000280287,0.0001188643,0.000008909461,0.0003669411,0.9960133,0.002247173],"study_design_scores_gemma":[0.0001707919,0.00001296521,0.02310177,0.0009213542,0.00006310207,0.00003250351,0.0005159125,0.0006029109,0.0001590195,0.0008225288,0.973507,0.00008993701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005857771,0.00005688765,0.00004553565,0.0001336259,0.0000371094,0.00002397227,0.9983401,0.00008981525,0.00121423],"genre_scores_gemma":[0.001180487,0.0003832497,0.0006962224,0.0001981086,0.00002547384,0.0002144133,0.9915807,0.000190117,0.005531315],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1122882,"threshold_uncertainty_score":0.3756413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460301565695989,"score_gpt":0.2289715443956255,"score_spread":0.2143685287386656,"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."}}