{"id":"W2920773083","doi":"10.3389/fpubh.2019.00138","title":"Valuing Health Surveillance as an Information System: Interdisciplinary Insights","year":2019,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"World Health Organization","keywords":"Risk analysis (engineering); Health informatics; Computer science; Value of information; Information system; Knowledge management; Health care; Management science; Data science; Medicine; Economics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002546301,0.0002608151,0.0009140504,0.0007717931,0.0001663044,0.000102104,0.0003259622,0.0001179461,0.00004208795],"category_scores_gemma":[0.0001561436,0.0002478018,0.00008456393,0.0008404951,0.00006170283,0.001648847,0.0002088457,0.0004175907,0.0002803206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002137241,"about_ca_system_score_gemma":0.002849646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003632145,"about_ca_topic_score_gemma":0.00009280317,"domain_scores_codex":[0.9962576,0.0006702406,0.001075342,0.0004802757,0.0006375986,0.0008789221],"domain_scores_gemma":[0.9972997,0.00003543105,0.0004942386,0.0009990555,0.0001756443,0.0009959367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004022276,0.0003750779,0.7399746,0.004738403,0.0001053499,0.00002884566,0.01257938,0.00005598094,0.000002524268,0.003173935,0.1006485,0.1379152],"study_design_scores_gemma":[0.004049458,0.001487525,0.7982204,0.0009266254,0.000004004555,0.00009848987,0.01655281,0.01827783,0.000001413691,0.0002536341,0.1596543,0.0004735107],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9176411,0.00216845,0.0174768,0.02735256,0.007444362,0.004483267,0.0003266206,0.00114302,0.02196382],"genre_scores_gemma":[0.9898723,0.0001312146,0.003504541,0.004601492,0.0001441726,0.00004552336,0.00152906,0.00003550329,0.0001362271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1374417,"threshold_uncertainty_score":0.9999974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667212212143463,"score_gpt":0.3025842404789351,"score_spread":0.2859121183575004,"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."}}