{"id":"W4206768996","doi":"10.1109/jtehm.2021.3137956","title":"A Computer Vision Approach to Identifying Ticks Related to Lyme Disease","year":2021,"lang":"en","type":"article","venue":"IEEE Journal of Translational Engineering in Health and Medicine","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; University of Toronto; Vector Institute; Response Biomedical (Canada); Public Health Ontario; Group Health Centre; Toronto Public Health","funders":"Vector Institute","keywords":"Lyme disease; Computer science; Artificial intelligence; Computer vision; Biology; Virology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004276407,0.0001143905,0.0003942398,0.0002989405,0.00003060394,0.000009344104,0.00004389493,0.00003596694,0.00001898248],"category_scores_gemma":[0.0001317092,0.00009411322,0.00006725147,0.0003057749,0.0000110278,0.00006365836,0.000005767747,0.0002133077,0.000001189262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004905192,"about_ca_system_score_gemma":0.0003448125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001088861,"about_ca_topic_score_gemma":9.394419e-7,"domain_scores_codex":[0.9985349,0.00002957737,0.0006642247,0.0001637209,0.0003985327,0.0002091076],"domain_scores_gemma":[0.9983668,0.00008914204,0.0000734139,0.00009414933,0.0001500119,0.001226435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.007795166,0.001747667,0.03035291,0.01011608,0.0005526143,0.002513671,0.01041282,0.7746146,0.00899444,0.006363344,0.006799111,0.1397376],"study_design_scores_gemma":[0.01854568,0.002890675,0.6274669,0.01138816,0.0002651583,0.00141674,0.000253914,0.3252072,0.0000395298,0.0003573691,0.01177642,0.0003922964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6793643,0.01824839,0.2426908,0.05774858,0.001111684,0.0006851605,0.000009773817,0.00002938766,0.0001119213],"genre_scores_gemma":[0.9888427,0.0002099441,0.007151714,0.003169296,0.0005385941,0.000005557458,0.00001573328,0.00001599996,0.00005050953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.597114,"threshold_uncertainty_score":0.3837826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01805322374452863,"score_gpt":0.3141560364627845,"score_spread":0.2961028127182559,"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."}}