{"id":"W2891521002","doi":"10.23889/ijpds.v3i4.942","title":"Data Linkage Methods in Manitoba","year":2018,"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":"Manitoba Health","funders":"","keywords":"Linkage (software); Computer science; Record linkage; Linked data; Data quality; Population; Data mining; Process (computing); Data science; Information retrieval; Engineering; Medicine","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":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03599566,0.0001013151,0.0001546328,0.0009385216,0.0004118771,0.002071756,0.01789373,0.00003482069,0.0002679356],"category_scores_gemma":[0.02074894,0.00007972484,0.00003058222,0.00100378,0.0003295294,0.01015859,0.004868643,0.0001582479,0.0001519227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001333947,"about_ca_system_score_gemma":0.0001622335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000363735,"about_ca_topic_score_gemma":0.003631703,"domain_scores_codex":[0.9949439,0.0002244588,0.001019263,0.0008845409,0.002646302,0.0002815993],"domain_scores_gemma":[0.9950602,0.0007788654,0.0005338503,0.002454837,0.001036702,0.0001355494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008785813,0.0001296392,0.02101122,0.000002479359,0.00002529572,0.00001423143,0.0001801966,0.0001142521,0.0006028654,0.03899502,0.07518413,0.8636528],"study_design_scores_gemma":[0.000460773,0.00004360995,0.1167308,0.00003007635,0.000007741967,0.00004494673,0.0005316772,0.148968,0.00008239586,0.07559175,0.6573492,0.0001590317],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01957095,0.00003188883,0.9566047,0.006056309,0.01269338,0.0003051713,0.002787275,0.00002668927,0.001923681],"genre_scores_gemma":[0.4436561,0.00005367993,0.5488387,0.001992421,0.002409393,0.000005950834,0.002111353,0.00001415269,0.000918191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8634938,"threshold_uncertainty_score":0.9989642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6645466192572466,"score_gpt":0.6439882190382802,"score_spread":0.02055840021896638,"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."}}