{"id":"W6976699279","doi":"10.6068/dp14ba7f9157715","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 73 years, In-migrants, Females | 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":[0.002065904,0.002285146,0.002558593,0.007315444,0.003139702,0.00453408,0.004939799,0.001247857,0.1111872],"category_scores_gemma":[0.01623799,0.001573967,0.00188651,0.03637223,0.0006136926,0.002304636,0.002473123,0.00296348,0.05707989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04636895,"about_ca_system_score_gemma":0.1205109,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945709,"about_ca_topic_score_gemma":0.9923759,"domain_scores_codex":[0.9967113,0.0002526265,0.0003764512,0.0004333559,0.00147357,0.0007527829],"domain_scores_gemma":[0.9742568,0.0008862911,0.0006854705,0.0007680623,0.02196839,0.001434936],"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":[0.00002085085,0.000005781376,0.0009605955,0.0002279519,0.0000192228,0.00000695205,0.00002924941,0.0001164338,0.000008917556,0.0003676728,0.9960126,0.002223861],"study_design_scores_gemma":[0.000173046,0.00001327035,0.0241045,0.0009406962,0.00006351913,0.00003282482,0.0005502313,0.0006024516,0.0001606633,0.0008138671,0.9724534,0.00009160591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005974033,0.00005725585,0.00004424748,0.0001361128,0.00003759542,0.00002427669,0.9983323,0.00008801432,0.0012205],"genre_scores_gemma":[0.001219127,0.0003905998,0.0006885065,0.000201172,0.00002576085,0.000219104,0.9914863,0.0001878012,0.00558167],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1111872,"threshold_uncertainty_score":0.3719581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829173445864277,"score_gpt":0.2374664458687269,"score_spread":0.2191747114100842,"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."}}