{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009124329,0.001139747,0.001273354,0.0002531082,0.0003054456,0.000761502,0.001110617,0.0007235166,0.0006928522],"category_scores_gemma":[0.0001270236,0.001181886,3.041279e-7,0.0005378958,0.0006657732,0.000791628,0.0005033304,0.0008620882,0.000009366372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003402898,"about_ca_system_score_gemma":0.004353103,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999967,"about_ca_topic_score_gemma":0.9999824,"domain_scores_codex":[0.9936322,0.0008384774,0.001187689,0.002034612,0.001378894,0.0009281418],"domain_scores_gemma":[0.9952026,0.0005540827,0.001028606,0.002271455,0.00007096641,0.0008722996],"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":[0.000184677,0.00009909205,0.001413918,0.0006296957,0.0003293683,0.0002058188,0.00001236541,0.000004195166,0.00001590122,0.0001515916,0.996686,0.0002674003],"study_design_scores_gemma":[0.001026175,0.000132073,0.000196335,0.00006968742,0.0007575576,0.0001817753,0.0003712124,0.005427513,1.287722e-8,7.98429e-7,0.9906009,0.001235893],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000303962,0.008519792,0.00001629756,0.000004400787,0.0004310296,0.00124347,0.9894522,0.0001301663,0.0001722824],"genre_scores_gemma":[0.000180275,0.002342259,0.000400084,0.0001798512,0.0002462224,0.00003577043,0.9952519,0.0003774083,0.0009862165],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006177533,"threshold_uncertainty_score":0.9990631,"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."}}