{"id":"W2804894071","doi":"10.5210/ojphi.v10i1.8987","title":"A Semantic Framework to Improve Interoperability of Malaria Surveillance Systems","year":2018,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of New Brunswick","funders":"Bill and Melinda Gates Foundation","keywords":"Interoperability; Computer science; Malaria; Metadata; Data science; Semantic interoperability; Data integration; Disease surveillance; Process management; Risk analysis (engineering); Data mining; World Wide Web; Medicine; Business; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005931527,0.000151929,0.0006443475,0.0003133642,0.00008625178,0.0001973677,0.001386626,0.0001015517,0.000006999819],"category_scores_gemma":[0.002789405,0.0001092375,0.00009319501,0.0006541149,0.00010195,0.0008973139,0.0003065948,0.0003639953,0.00001383035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000145289,"about_ca_system_score_gemma":0.00112272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006929147,"about_ca_topic_score_gemma":0.00003758516,"domain_scores_codex":[0.9962026,0.0002396108,0.002409365,0.00009995439,0.0005654438,0.000483013],"domain_scores_gemma":[0.995423,0.000289747,0.001711603,0.0006750487,0.001486017,0.0004146503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001410514,0.002213999,0.08976644,0.007125712,0.0005610426,0.00002467034,0.1017644,0.0005732861,0.0001728312,0.1553914,0.01957875,0.6226864],"study_design_scores_gemma":[0.003363135,0.01795864,0.2397605,0.003492011,0.00002699589,0.001386597,0.01973655,0.5687504,0.0002950003,0.005199971,0.1386717,0.001358606],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2197717,0.000159496,0.7637703,0.0137965,0.002149801,0.0002001825,0.00001306436,0.00003089714,0.0001080157],"genre_scores_gemma":[0.7639312,0.00005550839,0.2342208,0.001481139,0.0002902226,0.000001173896,9.027432e-7,0.000005381884,0.00001374378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6213278,"threshold_uncertainty_score":0.4454576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05504119652487432,"score_gpt":0.3388633850165383,"score_spread":0.283822188491664,"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."}}