{"id":"W3112904752","doi":"10.23889/ijpds.v5i5.1420","title":"Creation of First Nations Health Profiles Through Data Linkage in Manitoba","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"First Nations Health and Social Secretariat of Manitoba","funders":"","keywords":"Mandate; Information governance; Data sharing; Political science; Business; Public administration; Medicine; Information system; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0250586,0.0004956812,0.0005851201,0.008153251,0.006750071,0.004692153,0.003453799,0.001045788,0.01604889],"category_scores_gemma":[0.03532239,0.001019238,0.0006647127,0.01437077,0.001159521,0.00219384,0.008273405,0.001533165,0.003404356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02922793,"about_ca_system_score_gemma":0.1587375,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8150213,"about_ca_topic_score_gemma":0.8045282,"domain_scores_codex":[0.9899575,0.003275455,0.001186554,0.001276623,0.002946,0.001357712],"domain_scores_gemma":[0.9659878,0.003835986,0.002705572,0.004368401,0.01951266,0.003589598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004794783,0.0005888765,0.2662191,0.002233577,0.0003467137,0.001882495,0.02908089,0.002917148,0.002417698,0.04792213,0.3616883,0.2842237],"study_design_scores_gemma":[0.0001659162,0.0001217015,0.2601984,0.003210788,0.0001628889,0.0003652161,0.01845201,0.004336786,0.001856193,0.006712882,0.7042509,0.0001663967],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.322203,0.006076567,0.06002132,0.06311112,0.002447987,0.02563288,0.2680416,0.004727058,0.2477385],"genre_scores_gemma":[0.3967311,0.007479232,0.2405025,0.01573987,0.0004320586,0.03531817,0.1560258,0.001159783,0.1466115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1849787,"threshold_uncertainty_score":0.3721362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5272190626369835,"score_gpt":0.5404742119118103,"score_spread":0.01325514927482685,"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."}}