{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002370888,0.0003916147,0.0005737431,0.0003298838,0.001600135,0.0001046722,0.0002284097,0.00007483679,0.00119928],"category_scores_gemma":[0.0002293528,0.0004026439,0.0002457298,0.0003771209,0.0003716434,0.0001362681,0.0005214793,0.000389368,0.00003763559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001985439,"about_ca_system_score_gemma":0.0002603692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759011,"about_ca_topic_score_gemma":0.00007197213,"domain_scores_codex":[0.9972479,0.0006420452,0.0005738059,0.0007897194,0.0001087088,0.0006378493],"domain_scores_gemma":[0.998594,0.0001149716,0.0002357301,0.0004889015,0.0001030899,0.0004633215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002699289,0.026088,0.8713018,0.002244056,0.002966722,0.0002652375,0.003442637,0.0002862534,0.01393775,0.01961766,0.01478266,0.04236791],"study_design_scores_gemma":[0.003492493,0.001203024,0.9840541,0.0002476705,0.002496858,0.0001380516,0.001918947,0.0001119902,0.0000744644,0.0008290966,0.004535788,0.0008975354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705381,0.02230243,0.0003469575,0.0002712411,0.0002712338,0.001263805,0.004676016,0.0002562176,0.00007404466],"genre_scores_gemma":[0.9967503,0.0001051976,0.0001565485,0.0003614712,0.00005388826,0.0007295191,0.001229392,0.00006251023,0.0005511683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1127523,"threshold_uncertainty_score":0.9998425,"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."}}