{"id":"W2993407738","doi":"10.1007/s42650-019-00015-6","title":"Immigrant Health Data Development at Statistics Canada: an Update","year":2019,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"Immigration; Population; Settlement (finance); Geography; Demographic economics; Data science; Sociology; Demography; Computer science; Economics; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03995259,0.00244803,0.002918459,0.04489362,0.004051982,0.01108676,0.01098898,0.002287394,0.01643671],"category_scores_gemma":[0.1254949,0.002171604,0.00317774,0.1018089,0.002703816,0.004753095,0.005700164,0.00443657,0.007144977],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09059679,"about_ca_system_score_gemma":0.4015206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9890422,"about_ca_topic_score_gemma":0.988751,"domain_scores_codex":[0.9657965,0.003684026,0.007099521,0.00165669,0.01872596,0.003037341],"domain_scores_gemma":[0.6459234,0.03625479,0.01248681,0.01414548,0.2760335,0.01515608],"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":[0.00008338676,0.00004913882,0.01670892,0.001936291,0.0001578827,0.00005460716,0.0002848178,0.0003713726,0.00007820204,0.001478066,0.8872126,0.09158471],"study_design_scores_gemma":[0.00006522002,0.00001308528,0.04317516,0.005087485,0.0001897856,0.00007773573,0.0005472066,0.000306544,0.0003127621,0.0005109606,0.9496058,0.0001081077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005323525,0.06689459,0.006600953,0.06824376,0.008754905,0.001588712,0.7994749,0.004558516,0.03856011],"genre_scores_gemma":[0.03396324,0.1490681,0.03321346,0.02344987,0.003052258,0.002610363,0.7189735,0.003319802,0.03234936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9094032,"threshold_uncertainty_score":0.6573288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0961595447340438,"score_gpt":0.3871484373743503,"score_spread":0.2909888926403065,"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."}}