{"id":"W2161164234","doi":"10.1016/j.chom.2015.02.004","title":"Computational Approaches to Influenza Surveillance: Beyond Timeliness","year":2015,"lang":"en","type":"article","venue":"Cell Host & Microbe","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"U.S. National Library of Medicine; National Institute of Environmental Health Sciences; National Institutes of Health; Public Health Agency of Canada","keywords":"Biology; Computational biology; Virology; Data science; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004120547,0.0002527049,0.0004238996,0.0001335797,0.00005718258,0.00004710272,0.0002347028,0.00009220342,0.0001461099],"category_scores_gemma":[0.0001391358,0.0002426168,0.00009361083,0.0004021332,0.00009657702,0.00009528924,0.0001968022,0.0001698798,0.002173678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001270993,"about_ca_system_score_gemma":0.0003680609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003074683,"about_ca_topic_score_gemma":0.00001313477,"domain_scores_codex":[0.9983061,0.00007760241,0.0003736964,0.0004973391,0.0003635145,0.0003817369],"domain_scores_gemma":[0.9983846,0.0000754476,0.00009858072,0.0005361132,0.0003074658,0.0005978182],"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":[0.001583987,0.001557212,0.3262607,0.0006272433,0.0002157036,0.0002438256,0.002083749,0.009937697,0.02022286,0.0002548955,0.6305207,0.006491497],"study_design_scores_gemma":[0.0089007,0.0004295454,0.2171403,0.0001330337,0.0001001011,0.0001400096,0.0005270243,0.003488728,0.008291388,0.0003550175,0.7592823,0.00121184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970043,0.002162161,0.002968787,0.001777138,0.0005174375,0.001041975,0.0008609383,0.0003470227,0.02028155],"genre_scores_gemma":[0.9789249,0.000005753335,0.01235237,0.004783941,0.0003888037,0.00003394069,0.001546757,0.00007244541,0.00189109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1287616,"threshold_uncertainty_score":0.9986032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08883298094933957,"score_gpt":0.2862862964898796,"score_spread":0.19745331554054,"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."}}