{"id":"W6957778242","doi":"10.6068/dp14ba8098fca52","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 to 39 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":"","field":"","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":[0.002203342,0.00227274,0.002564633,0.007392535,0.003153675,0.004510223,0.00495118,0.001306802,0.1152884],"category_scores_gemma":[0.01782336,0.001657939,0.001948966,0.03716368,0.0006171054,0.002389465,0.002525992,0.003053804,0.0593321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04673003,"about_ca_system_score_gemma":0.1252011,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994501,"about_ca_topic_score_gemma":0.991947,"domain_scores_codex":[0.9964495,0.0002735193,0.000417697,0.0004541244,0.001606377,0.0007988222],"domain_scores_gemma":[0.9717324,0.0009716706,0.0007306081,0.00083923,0.02422772,0.001498418],"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":[0.00002248816,0.000006109941,0.0009647149,0.0002411766,0.00001908853,0.000006860858,0.00002987944,0.0001141952,0.000009264618,0.0003580152,0.9959,0.002328203],"study_design_scores_gemma":[0.0001753669,0.0000138643,0.0243257,0.0009599937,0.000063087,0.00003199488,0.0005596898,0.0005561637,0.0001577201,0.0008063288,0.9722568,0.0000933304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005899608,0.00005691107,0.00004618166,0.0001427239,0.00004012225,0.00002607739,0.9982692,0.00009154073,0.001268252],"genre_scores_gemma":[0.00123304,0.000410583,0.0007588692,0.0002274058,0.00002769263,0.0002400487,0.9908037,0.0002057032,0.006092945],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1152884,"threshold_uncertainty_score":0.3856781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400197034588302,"score_gpt":0.2329715854179999,"score_spread":0.2189696150721168,"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."}}