{"id":"W2130670679","doi":"10.4102/jsava.v78i1.280","title":"Seroprevalence of Babesia bigeminain smallholder dairy cattle in Tanzania and associated risk factors","year":2007,"lang":"en","type":"article","venue":"Journal of the South African Veterinary Association","topic":"Vector-borne infectious diseases","field":"Immunology and Microbiology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Department for International Development","keywords":"Seroprevalence; Veterinary medicine; Tanzania; Logistic regression; Biology; Livestock; Geography; Forestry; Serology; Medicine; Antibody; Immunology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.000389475,0.0001858986,0.0001608241,0.0006175078,0.0002407856,0.0002657472,0.0001709459,0.0002016666,0.0007221819],"category_scores_gemma":[0.000994108,0.0002672964,0.0001137307,0.0003636773,0.0003729406,0.0002010404,0.0002367928,0.0001671463,0.0001035002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003087496,"about_ca_system_score_gemma":0.0001491714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008350257,"about_ca_topic_score_gemma":0.01631505,"domain_scores_codex":[0.9998245,0.00006501161,0.00001652578,0.00003230655,0.00002126723,0.00004041351],"domain_scores_gemma":[0.9993603,0.0001397759,0.000288373,0.00002814886,0.00004532954,0.0001381838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005749554,0.00001932273,0.9977522,0.000007226051,0.000009786455,0.0001154507,0.0002925138,0.00002909989,0.0009783703,0.000007233608,0.00002453529,0.0007068832],"study_design_scores_gemma":[0.000002391928,0.00006806503,0.9995118,0.000002357114,0.000003968288,0.0001280382,0.0001749241,0.00005160485,0.00002939335,0.000003448248,0.00002288421,0.000001071901],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9999076,0.00003352578,0.000007680823,0.000005127702,3.508576e-7,8.733373e-7,0.00001458603,6.703918e-7,0.00002957043],"genre_scores_gemma":[0.9998959,0.00002156069,0.00002299001,0.000004231231,7.007303e-7,0.000001642437,0.00002095969,2.069611e-7,0.00003167247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008350257,"threshold_uncertainty_score":0.01660329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389979321072978,"score_gpt":0.2368543842601924,"score_spread":0.2229545910494626,"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."}}