{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2327823,0.0005652517,0.0008067349,0.00425367,0.00950991,0.00709832,0.00347943,0.002434807,0.009601215],"category_scores_gemma":[0.2004047,0.0009755215,0.0009333068,0.004206804,0.004195248,0.008802185,0.02123143,0.0031468,0.001161874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008048626,"about_ca_system_score_gemma":0.04775294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02191623,"about_ca_topic_score_gemma":0.06853565,"domain_scores_codex":[0.8098003,0.1711852,0.004747662,0.003768676,0.005281006,0.005217171],"domain_scores_gemma":[0.7816302,0.137837,0.01733239,0.01975448,0.03074486,0.01270099],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003003315,0.0009667702,0.08917669,0.006987576,0.0002964277,0.001221505,0.5679105,0.0004193229,0.001909574,0.01654826,0.02953296,0.28473],"study_design_scores_gemma":[0.0001778801,0.0005728137,0.03968351,0.01237007,0.0001856195,0.0005377844,0.7552865,0.00139,0.001612008,0.02172644,0.1663017,0.0001556287],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5491984,0.01307871,0.1383325,0.1769245,0.002534353,0.04086158,0.005508441,0.0007917926,0.07276963],"genre_scores_gemma":[0.7611253,0.00368852,0.1659713,0.02140572,0.0004192771,0.03760618,0.001412789,0.0002011196,0.008169856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7672177,"threshold_uncertainty_score":0.946116,"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."}}