{"id":"W2794390659","doi":"10.3389/fvets.2018.00002","title":"A Smartphone-Based Application Improves the Accuracy, Completeness, and Timeliness of Cattle Disease Reporting and Surveillance in Ethiopia","year":2018,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"International Development Research Centre","keywords":"Disease; Disease surveillance; Outbreak; Smartphone application; Computer science; Disease monitoring; Smartphone app; Disease control; Cloud server; Medicine; Environmental health; Medical emergency; Cloud computing; Internet privacy; Pathology","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":[0.00135257,0.00007336418,0.0001493009,0.00003428163,0.0001509367,0.00002324105,0.0002278916,0.00002233735,0.000003420303],"category_scores_gemma":[0.000666786,0.0000304306,0.00001534077,0.0005375601,0.001050395,0.0001333301,0.0001528028,0.00004943535,5.236897e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001316373,"about_ca_system_score_gemma":0.00002180456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003142079,"about_ca_topic_score_gemma":0.0001218584,"domain_scores_codex":[0.9990047,0.00008147513,0.0003163747,0.000307717,0.0001016089,0.0001881575],"domain_scores_gemma":[0.9994192,0.0001493413,0.0002572365,0.00007756146,0.00004164883,0.00005501575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000133526,0.00002328904,0.9112685,0.00002211955,8.947514e-7,0.000002426649,0.00004476115,0.000007634129,0.05617137,0.00007302007,0.00007937545,0.0321731],"study_design_scores_gemma":[0.00007371957,0.0001469586,0.9757199,0.0000147801,0.000001337076,0.000001051858,0.0001448157,0.02271846,0.00002887739,0.0004619778,0.0006207051,0.0000673846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980339,0.0002662301,0.0002707324,0.001074031,0.00009569107,0.000189581,0.000006539169,0.000009249319,0.00005404279],"genre_scores_gemma":[0.9991422,0.00003262518,0.000564256,0.000194928,0.00003350032,0.00001690887,0.000006487669,4.888831e-7,0.000008618948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06445145,"threshold_uncertainty_score":0.3870224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03714701410269126,"score_gpt":0.2853898819774304,"score_spread":0.2482428678747391,"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."}}