{"id":"W6920418433","doi":"10.6068/dp14ba7fdf72859","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 0 to 4 years, Out-migrants, 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; Economic statistics; Demographic 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":[0.002172207,0.00227131,0.002519937,0.007302235,0.003110129,0.004470801,0.004904912,0.001235537,0.1136958],"category_scores_gemma":[0.0168571,0.001611306,0.001951962,0.03628561,0.0006156476,0.002300328,0.002446647,0.002959959,0.05728009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04714654,"about_ca_system_score_gemma":0.123713,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946361,"about_ca_topic_score_gemma":0.9924155,"domain_scores_codex":[0.9965867,0.0002628349,0.0003899432,0.0004411328,0.001542944,0.0007765092],"domain_scores_gemma":[0.9728255,0.0009242584,0.0006981743,0.0008018399,0.0233038,0.001446487],"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":[0.0000221251,0.000006060724,0.001009389,0.0002423632,0.00001998116,0.000007293324,0.00003060053,0.0001200554,0.00000941312,0.0003662777,0.9958242,0.002342221],"study_design_scores_gemma":[0.000171046,0.00001363753,0.02518119,0.0009507863,0.00006454016,0.00003360039,0.0005654946,0.0005797096,0.000161292,0.0008126392,0.9713737,0.0000923584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006143682,0.00005794934,0.00004502885,0.000136667,0.00003785832,0.00002489474,0.9983164,0.00008996494,0.001229948],"genre_scores_gemma":[0.001278726,0.0003978465,0.0007449886,0.0002085317,0.00002614689,0.0002290015,0.9909457,0.0002010337,0.005967871],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1136958,"threshold_uncertainty_score":0.3803502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755883215832457,"score_gpt":0.2382625684706379,"score_spread":0.2207037363123133,"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."}}