{"id":"W3015874364","doi":"10.48550/arxiv.2004.04596","title":"Global Public Health Surveillance using Media Reports: Redesigning GPHIN","year":2020,"lang":"en","type":"preprint","venue":"PubMed","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Underpinning; Mainstream; Trustworthiness; Public health; Politics; Public relations; Political science; Public health surveillance; Computer science; Internet privacy; Engineering; 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":[0.05927653,0.001360845,0.0009435666,0.006101436,0.0007474967,0.01067161,0.004508235,0.00207465,0.004850857],"category_scores_gemma":[0.152412,0.001553076,0.00145491,0.00361042,0.002614602,0.01765871,0.008369769,0.003808649,0.003491702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00138922,"about_ca_system_score_gemma":0.004525932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002437462,"about_ca_topic_score_gemma":0.001654588,"domain_scores_codex":[0.9656656,0.01940342,0.004230184,0.003914235,0.005935414,0.0008511697],"domain_scores_gemma":[0.8073643,0.08298569,0.008831441,0.06623969,0.03056861,0.004010285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001237173,0.0005252651,0.01930816,0.002290183,0.0003250588,0.0006595294,0.005914704,0.006612159,0.01016364,0.08921969,0.0391159,0.8246285],"study_design_scores_gemma":[0.0005985713,0.001401409,0.01214785,0.002898384,0.0007695647,0.0009744185,0.002849348,0.06711325,0.02736704,0.08657546,0.7967575,0.0005472616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04126339,0.002711144,0.8526688,0.01670655,0.003674732,0.005363953,0.002687548,0.04711518,0.02780882],"genre_scores_gemma":[0.1576161,0.002130067,0.8144324,0.004044425,0.001326264,0.002261234,0.00565231,0.003810322,0.008726898],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05927653,"threshold_uncertainty_score":0.313488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376487322422343,"score_gpt":0.3181640899197627,"score_spread":0.1805153576775285,"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."}}