{"id":"W4225271889","doi":"10.3390/pathogens11050531","title":"Sentinel Surveillance Contributes to Tracking Lyme Disease Spatiotemporal Risk Trends in Southern Quebec, Canada","year":2022,"lang":"en","type":"article","venue":"Pathogens","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Université de Montréal; University of Saskatchewan; Santé Montérégie; Centre Intégré de Santé et de Services Sociaux des Laurentides; Public Health Agency of Canada; Université de Sherbrooke","funders":"","keywords":"Enzootic; Public health; Geography; Poisson regression; Environmental health; Lyme disease; Risk assessment; Hazard; Medicine; Ecology; Population; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001448118,0.0003617018,0.000219254,0.001174869,0.001094281,0.001033654,0.0008911687,0.0002063426,0.002905682],"category_scores_gemma":[0.004304147,0.000172977,0.0002718864,0.00178552,0.0002366887,0.0003492216,0.0005304506,0.0002935659,0.0002227784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01920028,"about_ca_system_score_gemma":0.0311081,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962425,"about_ca_topic_score_gemma":0.9972911,"domain_scores_codex":[0.9992464,0.0001707634,0.00003242135,0.0001300256,0.0002252519,0.0001952072],"domain_scores_gemma":[0.9970668,0.000295028,0.0003611386,0.0001111157,0.00183797,0.0003280067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001354228,0.00007202611,0.9179307,0.0001077232,0.0001102304,0.0001230523,0.0009005827,0.0068669,0.0008873052,0.000514725,0.01121193,0.06113941],"study_design_scores_gemma":[0.00002628854,0.00009070829,0.9329399,0.0001867962,0.0001018968,0.00008049072,0.002747267,0.04864792,0.0005374574,0.0002444273,0.01436124,0.00003561191],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577749,0.001644344,0.007303247,0.002053834,0.00006484956,0.0002831831,0.01532403,0.0002954098,0.01525626],"genre_scores_gemma":[0.9902691,0.000504631,0.003572415,0.0001327777,0.000009266734,0.00004599262,0.002696781,0.00001888631,0.002750236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01920028,"threshold_uncertainty_score":0.1393085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008249931038739302,"score_gpt":0.2164274897292705,"score_spread":0.2081775586905312,"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."}}