{"id":"W4312242765","doi":"10.2196/42292","title":"Big Data and Infectious Disease Epidemiology: Bibliometric Analysis and Research Agenda","year":2022,"lang":"en","type":"article","venue":"Interactive Journal of Medical Research","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Disease surveillance; Data science; Infectious disease (medical specialty); Informatics; Epidemiology; Disease; Pandemic; Health informatics; The Internet; Public health; Medicine; Computer science; Political science; Coronavirus disease 2019 (COVID-19); World Wide Web; Data mining; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0258188,0.0009653608,0.002388871,0.111226,0.002788191,0.01610317,0.001295564,0.002044328,0.003275384],"category_scores_gemma":[0.08037587,0.0004895343,0.001332382,0.1665131,0.004243781,0.01456171,0.003336817,0.001464911,0.0004264188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007664213,"about_ca_system_score_gemma":0.01423205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007826701,"about_ca_topic_score_gemma":0.008778997,"domain_scores_codex":[0.9815357,0.009623623,0.001543039,0.0008787066,0.005851567,0.0005673483],"domain_scores_gemma":[0.8814325,0.09058195,0.01021761,0.003540199,0.01255723,0.001670571],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001522631,0.0002374021,0.1674983,0.02190479,0.001188062,0.0004768042,0.005717061,0.004274429,0.000482893,0.2117556,0.04778981,0.5385225],"study_design_scores_gemma":[0.00007824859,0.0002328227,0.1922247,0.03623978,0.001125485,0.001503409,0.04374829,0.01955951,0.001420814,0.3833643,0.3202061,0.0002965158],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.1044858,0.5501314,0.02796431,0.2305323,0.002873237,0.0009052551,0.007542572,0.000362961,0.07520214],"genre_scores_gemma":[0.5430804,0.4105746,0.03041271,0.004728512,0.005101154,0.0006762802,0.003501538,0.00006650939,0.001858318],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9741812,"threshold_uncertainty_score":0.1365445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3080709112029464,"score_gpt":0.5562182349421962,"score_spread":0.2481473237392499,"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."}}