{"id":"W2893214481","doi":"10.3390/su10103414","title":"Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization","year":2018,"lang":"en","type":"article","venue":"Sustainability","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Iran Telecommunication Research Center; National Research Foundation of Korea; Ministry of Science, ICT and Future Planning; National Research Foundation","keywords":"Scopus; Bibliometrics; Data science; Web of science; Flourishing; Citation; Citation analysis; Publishing; Visualization; Field (mathematics); Analytics; Computer science; Library science; Data mining; MEDLINE; Political science; Psychology","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":["metaresearch","bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.002469177,0.0001962772,0.0005303059,0.01861754,0.0002076158,0.00009468884,0.000236127,0.000112827,0.000247061],"category_scores_gemma":[0.00875792,0.0001818534,0.0001109366,0.151785,0.0004342945,0.0001241425,0.0002931399,0.0001421562,0.0001274612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001512188,"about_ca_system_score_gemma":0.0004775094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005205865,"about_ca_topic_score_gemma":0.001779277,"domain_scores_codex":[0.9966328,0.0006228552,0.0003627856,0.0009846835,0.0008005718,0.0005963655],"domain_scores_gemma":[0.9946054,0.0004653958,0.00007395769,0.00134171,0.002993321,0.0005202604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007242039,0.000247816,0.9843161,0.00009400279,0.000208066,0.0000447137,0.00006773925,0.00001250954,0.0000169848,0.0003713729,0.005400283,0.008496171],"study_design_scores_gemma":[0.0005755117,0.0005681488,0.9923052,0.00001535392,0.00008826284,0.000002745942,0.0001577268,0.0005368,0.00004175503,0.002812321,0.002731044,0.0001651014],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946591,0.0002038226,0.001527879,0.0009417175,0.00009216207,0.0008810299,0.0006815193,0.0001344062,0.0008783122],"genre_scores_gemma":[0.9988174,0.00003051205,0.0001848292,0.000217595,0.0001713124,0.00003623313,0.00036566,0.0000158782,0.0001605647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1331674,"threshold_uncertainty_score":0.9995917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04081826464100322,"score_gpt":0.4362929666343069,"score_spread":0.3954747019933037,"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."}}