{"id":"W6938877037","doi":"10.6068/dp14ba7f919ab18","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 19 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":[0.002067376,0.002278111,0.002551132,0.007294686,0.003160656,0.00456256,0.004948453,0.001245298,0.1117691],"category_scores_gemma":[0.01620671,0.001568845,0.001888962,0.03636961,0.0006160904,0.002315049,0.002485294,0.002975525,0.05755293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04642534,"about_ca_system_score_gemma":0.121172,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994594,"about_ca_topic_score_gemma":0.9923806,"domain_scores_codex":[0.9966992,0.0002541236,0.0003773517,0.000434823,0.001481493,0.0007530496],"domain_scores_gemma":[0.9742866,0.0008846955,0.0006808475,0.0007668291,0.02195028,0.001430665],"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":[0.00002061895,0.00000577946,0.0009484209,0.0002276454,0.00001908436,0.000006946154,0.00002952342,0.0001156275,0.000008933237,0.0003720028,0.9960186,0.002226714],"study_design_scores_gemma":[0.0001687374,0.00001298403,0.02353203,0.0009250445,0.00006233341,0.0000323235,0.0005495372,0.0005904995,0.0001592523,0.0008064143,0.9730704,0.00009052279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005943343,0.00005702411,0.00004452352,0.0001368077,0.00003784342,0.0000242795,0.9983164,0.00008848886,0.001235296],"genre_scores_gemma":[0.001213167,0.0003900616,0.0006986476,0.0002025274,0.00002568561,0.0002189626,0.9913994,0.0001905113,0.005660913],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1117691,"threshold_uncertainty_score":0.3739048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893576141416043,"score_gpt":0.2396624995749919,"score_spread":0.2207267381608315,"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."}}