{"id":"W2884011204","doi":"10.14745/ccdr.v41i09a03","title":"Big Data is changing the battle against infectious diseases","year":2015,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Agriculture and Agri-Food Canada","funders":"Canadian Institutes of Health Research; Agriculture and Agri-Food Canada; Government of Canada","keywords":"Big data; Bespoke; Battle; Multidisciplinary approach; Data science; Computer science; Infectious disease (medical specialty); Computer security; Business; Disease; Medicine; Political science; Geography; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02081644,0.001099403,0.001515535,0.003508778,0.003270101,0.01636727,0.002525939,0.006357285,0.01029603],"category_scores_gemma":[0.0604996,0.0006186757,0.001036099,0.00439032,0.008582503,0.02306708,0.007658293,0.01108355,0.00544072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003604841,"about_ca_system_score_gemma":0.01169901,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006880046,"about_ca_topic_score_gemma":0.006516091,"domain_scores_codex":[0.9869266,0.004766881,0.0006986146,0.0009786304,0.005880317,0.0007489172],"domain_scores_gemma":[0.9549509,0.02227139,0.002310575,0.003762586,0.009391531,0.007312957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001816923,0.00008682514,0.004617046,0.001141916,0.0002235646,0.0001651833,0.000716742,0.001226791,0.0006480055,0.1924335,0.5783272,0.2202314],"study_design_scores_gemma":[0.00002609078,0.00005635188,0.001702387,0.001298157,0.00004204809,0.0001273741,0.001044104,0.000942097,0.0002762918,0.2095938,0.7848355,0.00005580037],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002339828,0.07480744,0.01451478,0.8595856,0.02458373,0.00006383651,0.001221354,0.0006199397,0.02226355],"genre_scores_gemma":[0.1318599,0.2762252,0.05442533,0.4197581,0.09427602,0.0002581013,0.003252942,0.0009236501,0.01902073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.99312,"threshold_uncertainty_score":0.1100892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0800135105782911,"score_gpt":0.293943672934306,"score_spread":0.2139301623560149,"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."}}