{"id":"W2167752508","doi":"10.5210/ojphi.v5i1.4401","title":"Determinants of Outbreak Detection Performance","year":2013,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Computer science; Outbreak; Data mining; Bayesian probability; Selection (genetic algorithm); Set (abstract data type); Data set; Machine learning; Artificial intelligence; Algorithm; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.02259696,0.0006139653,0.0007064941,0.002233293,0.0004102713,0.00304878,0.0007193654,0.001407476,0.001134949],"category_scores_gemma":[0.1855833,0.0004098053,0.0006335223,0.001755547,0.0009166009,0.002607941,0.00087525,0.001268403,0.00034106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009874804,"about_ca_system_score_gemma":0.001136375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002276515,"about_ca_topic_score_gemma":0.001293837,"domain_scores_codex":[0.9906623,0.004978289,0.0008769882,0.00142787,0.001229816,0.0008247806],"domain_scores_gemma":[0.7131905,0.2558749,0.01015339,0.008922867,0.009895588,0.001962794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009950864,0.0006804583,0.5791889,0.0003151036,0.0006944209,0.0002150726,0.0003158928,0.3111465,0.005950521,0.006852774,0.001504783,0.09214057],"study_design_scores_gemma":[0.00005908099,0.0006091786,0.2286509,0.00007631123,0.0001565472,0.0004168945,0.0002315809,0.7470903,0.01128036,0.01041825,0.0009142203,0.00009641639],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9412304,0.0006971245,0.05308336,0.000784225,0.00003050347,0.0001487704,0.0005289109,0.0003462485,0.003150477],"genre_scores_gemma":[0.9931218,0.0000806188,0.006402803,0.00002518108,0.000009239901,0.00002033986,0.0002020706,0.00002585912,0.0001121048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02259696,"threshold_uncertainty_score":0.1195055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04793860230450372,"score_gpt":0.3369494116659609,"score_spread":0.2890108093614572,"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."}}