{"id":"W7131237326","doi":"10.5281/zenodo.18761790","title":"Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Time-Series Forecasting Models","year":2003,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Public health; Public health interventions; Quarter (Canadian coin); Disease surveillance; Psychological intervention; Public health surveillance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1478517,0.001037339,0.001160389,0.002241144,0.0012664,0.001900217,0.002305921,0.001264751,0.001356196],"category_scores_gemma":[0.3176992,0.0007980156,0.002664449,0.0034394,0.001090136,0.001533306,0.002771622,0.001224961,0.0001036534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004775304,"about_ca_system_score_gemma":0.00445759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06686331,"about_ca_topic_score_gemma":0.02543217,"domain_scores_codex":[0.8373072,0.1491975,0.006230383,0.003858902,0.00242298,0.0009830981],"domain_scores_gemma":[0.6484931,0.3096252,0.01491469,0.01415284,0.01195218,0.0008619518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004439796,0.0009023124,0.2325094,0.001259602,0.004794006,0.0003774154,0.002720265,0.6138936,0.0007593933,0.02717799,0.001264086,0.1099022],"study_design_scores_gemma":[0.0008654133,0.00217273,0.05312057,0.0002756129,0.001288635,0.00009672469,0.001755529,0.9255194,0.002054859,0.01025363,0.002481962,0.0001149472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7896534,0.001195003,0.2001334,0.001140138,0.0001647626,0.00343933,0.001603712,0.0002238564,0.00244647],"genre_scores_gemma":[0.9278039,0.0002208706,0.06796309,0.00009370481,0.00002718088,0.002790675,0.0008326743,0.00001630109,0.0002516261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1478517,"threshold_uncertainty_score":0.781924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4636927743555923,"score_gpt":0.3791099598868584,"score_spread":0.08458281446873389,"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."}}