{"id":"W2032230207","doi":"10.1186/1471-2458-12-929","title":"The use of syndromic surveillance for decision-making during the H1N1 pandemic: A qualitative study","year":2012,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Kingston Health Sciences Centre; McMaster University; University of Toronto; Public Health Ontario","funders":"Institute of Population and Public Health; Canadian Institutes of Health Research","keywords":"Medicine; Biostatistics; Pandemic; Public health; Qualitative research; Epidemiology; H1n1 pandemic; Public health surveillance; Environmental health; Coronavirus disease 2019 (COVID-19); Medical emergency; Infectious disease (medical specialty); Disease; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008572358,0.0001890093,0.0005294682,0.00009440645,0.0004860823,0.00007192091,0.0003379623,0.00004586498,0.00002001382],"category_scores_gemma":[0.01088683,0.0001053607,0.0001431581,0.0004190112,0.000151406,0.0003099198,0.0001588459,0.000203772,0.00001325589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003178187,"about_ca_system_score_gemma":0.0009184162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001508019,"about_ca_topic_score_gemma":0.001018276,"domain_scores_codex":[0.9960613,0.001387307,0.0008234456,0.000315539,0.0005600691,0.0008523436],"domain_scores_gemma":[0.9874398,0.01035871,0.0005048121,0.001058132,0.0002930702,0.0003454527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005612519,0.0005824862,0.9610592,0.000314195,0.00015969,0.000001377493,0.01788518,0.000008046874,0.00001050842,0.0004206484,0.003672404,0.01532507],"study_design_scores_gemma":[0.00135474,0.0002238402,0.9589236,0.000135245,0.00001248867,0.00003277425,0.01391321,0.0002335087,6.730349e-7,0.00005309855,0.02498863,0.0001281319],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900351,0.001166535,0.004347545,0.001134706,0.0003138179,0.002505001,0.0003775808,0.0000941565,0.00002555483],"genre_scores_gemma":[0.9970203,0.00009187289,0.00195408,0.0003857579,0.0001695946,0.0002066162,0.00002720467,0.00003772282,0.0001068424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02131622,"threshold_uncertainty_score":0.9974449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1554256629311621,"score_gpt":0.4386711743245237,"score_spread":0.2832455113933616,"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."}}