{"id":"W1456001213","doi":"","title":"A Comparison of National Health Data Interoperability Approaches in Taiwan, Denmark and Canada","year":2011,"lang":"en","type":"article","venue":"ElectronicHealthcare","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interoperability; Mandate; Government (linguistics); Cross-domain interoperability; Demographics; Affect (linguistics); Semantic interoperability; Work (physics); Population; Business; Computer science; Political science; Environmental health; World Wide Web; Medicine; Engineering; Demography; Sociology; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004475198,0.0002562218,0.0009175493,0.0001625917,0.0003721826,0.000003423653,0.0006571707,0.000226768,0.0001177139],"category_scores_gemma":[0.0004897989,0.000245953,0.00002405551,0.0003787772,0.00008588706,0.0001689578,0.0003072378,0.001838401,0.000007262925],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005003981,"about_ca_system_score_gemma":0.03882959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8620517,"about_ca_topic_score_gemma":0.9953936,"domain_scores_codex":[0.9927626,0.002410134,0.001947461,0.0007765581,0.0005800371,0.00152324],"domain_scores_gemma":[0.9973785,0.0003569258,0.0007614943,0.0008694789,0.0002693947,0.0003641839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001486667,0.0001505514,0.9678122,0.002414336,0.00002534458,9.866138e-7,0.01306975,0.000001002409,0.000008553348,0.002990899,0.006631345,0.006746313],"study_design_scores_gemma":[0.003857528,0.002275136,0.883966,0.001710442,0.00001539802,0.00002496417,0.05834239,0.006938371,0.0001267557,0.002173047,0.03958129,0.0009887201],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9608177,0.01806743,0.0001256239,0.01205165,0.0005707928,0.003234383,0.0002627353,0.00006335329,0.004806324],"genre_scores_gemma":[0.9977846,0.0001295331,0.0003786312,0.001107426,0.000111438,0.0001755772,0.0001437374,0.0000381207,0.0001309703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1333419,"threshold_uncertainty_score":0.9999993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4213569423431938,"score_gpt":0.4862343281172483,"score_spread":0.0648773857740545,"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."}}