{"id":"W4309565052","doi":"10.1016/j.ttbdis.2022.102083","title":"Integrated human behavior and tick risk maps to prioritize Lyme disease interventions using a 'One Health' approach","year":2022,"lang":"en","type":"article","venue":"Ticks and Tick-borne Diseases","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Santé Montérégie; Université de Montréal; Cegep de Saint Hyacinthe; Public Health Agency of Canada","funders":"Université de Montréal; Institut National de Santé Publique du Québec; Public Health Agency; Public Health Agency of Canada","keywords":"Lyme disease; Ixodes scapularis; Population; Environmental health; Psychological intervention; Public health; Geography; Risk perception; Environmental resource management; Tick; Ecology; Psychology; Biology; Medicine; Perception","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00145526,0.0008958977,0.0006394669,0.004406667,0.0004356339,0.001572533,0.001029589,0.000606072,0.00285781],"category_scores_gemma":[0.006763224,0.0004851831,0.000845183,0.001864467,0.0004681203,0.0008907315,0.001629806,0.0004749555,0.0002008521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00211281,"about_ca_system_score_gemma":0.002394842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09257165,"about_ca_topic_score_gemma":0.1050869,"domain_scores_codex":[0.9991722,0.0004491695,0.00003821386,0.0001377253,0.0001333922,0.00006924396],"domain_scores_gemma":[0.9977774,0.001363487,0.0002642567,0.0001298806,0.0003699759,0.00009498664],"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":[0.0002353304,0.0004437007,0.08438271,0.0004464593,0.0005529159,0.0002583718,0.001145444,0.7523233,0.002148037,0.0130083,0.001662863,0.1433926],"study_design_scores_gemma":[0.00002276935,0.000123958,0.02467449,0.00005864175,0.0001099217,0.00005701805,0.0007585196,0.9610834,0.0005378507,0.01050401,0.002031191,0.00003812694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3037713,0.0005283671,0.6812848,0.000902866,0.00004052041,0.0006771956,0.002991297,0.001623474,0.008180049],"genre_scores_gemma":[0.7355827,0.0002202874,0.2612352,0.00006726142,0.0000154817,0.0003006832,0.001118582,0.00006131544,0.001398463],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09257165,"threshold_uncertainty_score":0.1840656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03225865931772644,"score_gpt":0.2969081794669296,"score_spread":0.2646495201492032,"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."}}