{"id":"W4294243194","doi":"10.23889/ijpds.v7i3.1879","title":"Engaging im/migrant communities in cross-sectoral health and immigration data linkage research.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Simon Fraser University; University of British Columbia; Hospital for Sick Children; Dalhousie University","funders":"","keywords":"Immigration; Linkage (software); Political science; Data science; Computer science; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01437809,0.00009463455,0.0001309637,0.0008863874,0.002638225,0.0005409385,0.003027778,0.00002757823,0.0002476608],"category_scores_gemma":[0.0004791849,0.00009664647,0.00001708462,0.0005275696,0.0002557959,0.002444387,0.001166631,0.0007617624,0.000004586185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003388596,"about_ca_system_score_gemma":0.0005153675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01937519,"about_ca_topic_score_gemma":0.01305826,"domain_scores_codex":[0.9966232,0.0006083469,0.0006766678,0.0004451219,0.001202672,0.0004439782],"domain_scores_gemma":[0.997872,0.00038213,0.0003111771,0.000883699,0.0003508944,0.0002000752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005476511,0.00032384,0.8460644,0.00003285186,0.00003350272,0.00001910924,0.0458721,0.000693685,0.00006387565,0.02671985,0.01624683,0.06338233],"study_design_scores_gemma":[0.00200979,0.0003281076,0.7516936,0.00007023872,0.000003750162,0.0004119061,0.02934449,0.1016002,0.000002171812,0.004521398,0.1097799,0.0002344211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857432,0.0009891591,0.002497313,0.004749126,0.00330342,0.0004260784,0.002198049,0.00002275112,0.00007092186],"genre_scores_gemma":[0.9914808,0.0001437976,0.001287623,0.0005989287,0.0003190508,0.00002997303,0.006013513,0.0000112801,0.0001149992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1009065,"threshold_uncertainty_score":0.9986602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.360864436101784,"score_gpt":0.556281129751645,"score_spread":0.195416693649861,"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."}}