{"id":"W1537261845","doi":"10.22201/cisan.24487228e.2011.1.128","title":"Dossier: Mexican Migration to Canada Statistical Data and Interview With Chona Iturralde, Citizenship and Immigration Canada ( CIC )","year":2011,"lang":"en","type":"article","venue":"Redalyc (Universidad Autónoma del Estado de México)","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Immigration policy; Per capita; Refugee; Citizenship; Political science; Settlement (finance); Government (linguistics); Geography; Demographic economics; Recession; Economic growth; Population; Business; Demography; Sociology; Economics; Politics; Payment","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":[0.001497166,0.0004365364,0.0003996083,0.004533362,0.007545152,0.002466888,0.00149043,0.0009413344,0.02528873],"category_scores_gemma":[0.005275335,0.0005762142,0.0003293235,0.008460883,0.0006097209,0.0008206309,0.001715362,0.001667125,0.004755301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03726448,"about_ca_system_score_gemma":0.07346942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926915,"about_ca_topic_score_gemma":0.9937927,"domain_scores_codex":[0.9990003,0.00007303552,0.00006193451,0.00009746398,0.0003541378,0.0004131057],"domain_scores_gemma":[0.9958787,0.0003892554,0.0002365402,0.000131473,0.002749212,0.0006148224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002713184,0.00004596845,0.01935958,0.0001006982,0.000005903539,0.0001326369,0.004804634,0.00009500898,0.00006645967,0.001352401,0.9618983,0.01211125],"study_design_scores_gemma":[0.00002481435,0.00001776393,0.2241689,0.0004069216,0.00001009804,0.00007040633,0.03122113,0.0003101432,0.0001601934,0.0002284152,0.7433103,0.00007097153],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.08286034,0.002423463,0.0007063922,0.0353643,0.0009223433,0.002083132,0.7424651,0.0002710274,0.132904],"genre_scores_gemma":[0.2750106,0.008691159,0.004117183,0.01832522,0.0003630263,0.009065244,0.326723,0.000380809,0.3573237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03726448,"threshold_uncertainty_score":0.270374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692535568448644,"score_gpt":0.2506940952816814,"score_spread":0.2237687395971949,"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."}}