{"id":"W4283528853","doi":"10.1111/cag.12785","title":"Geo‐scripts and refugee resettlement in Canada: Designations and destinations","year":2022,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Refugee; Government (linguistics); Settlement (finance); Livelihood; Economic growth; Political science; Immigration; Displaced person; Destinations; Geography; Business; Law; Tourism; Economics; Agriculture","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0006986537,0.0002089405,0.0002159491,0.002754723,0.003263532,0.0001360432,0.0002688366,0.00006221904,0.000250881],"category_scores_gemma":[0.0002850484,0.0002496363,0.00004800257,0.003589131,0.000723615,0.0003230975,0.00004835398,0.0002667244,3.331902e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115018,"about_ca_system_score_gemma":0.003092227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9996784,"about_ca_topic_score_gemma":0.9999996,"domain_scores_codex":[0.997652,0.0003229806,0.0003581306,0.0004300851,0.0004119348,0.000824851],"domain_scores_gemma":[0.9985686,0.0001686376,0.0001021927,0.000214482,0.0001763195,0.0007697854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001354927,0.00002871397,0.6631882,0.00002584331,0.00006922664,0.00007726887,0.02412596,0.0001081967,0.00002442491,0.255317,0.04261358,0.01440806],"study_design_scores_gemma":[0.0002591154,0.00006954683,0.3885254,0.00001802417,0.00002553826,0.0000142633,0.08502037,0.00008261488,0.000002108942,0.004851501,0.5207492,0.0003823439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863692,0.003310041,0.000004362586,0.005604565,0.0004506325,0.0005904563,0.0004003593,0.00003645416,0.003233919],"genre_scores_gemma":[0.9963717,0.001748624,0.0001266139,0.0007483079,0.00005558199,0.0003039559,0.0001230843,0.00001919686,0.0005029254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4781356,"threshold_uncertainty_score":0.9999956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314125892296892,"score_gpt":0.2220523536660001,"score_spread":0.2089110947430312,"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."}}