{"id":"W2163193677","doi":"10.1186/1756-3305-6-138","title":"Spatio-temporal analysis to identify determinants of Oncomelania hupensis infection with Schistosoma japonicum in Jiangsu province, China","year":2013,"lang":"en","type":"article","venue":"Parasites & Vectors","topic":"Parasites and Host Interactions","field":"Immunology and Microbiology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention; Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China; International Development Research Centre","keywords":"Oncomelania hupensis; Snail; Biology; Schistosoma japonicum; Oncomelania; Livestock; SCHISTOSOMIASIS JAPONICA; Spatial distribution; China; Schistosomiasis; Ecology; Schistosoma; Spatial analysis; Veterinary medicine; Geography; Zoology; Helminths; Schistosoma mansoni","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001172821,0.0002265087,0.0005223509,0.0008371747,0.0001214676,0.00003396189,0.0001610615,0.0001529226,0.00132715],"category_scores_gemma":[0.00006123441,0.0001908877,0.0001555403,0.001021843,0.00008996526,0.0002971427,0.00005058345,0.0002325369,0.0008636106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001105083,"about_ca_system_score_gemma":0.00005216557,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03039993,"about_ca_topic_score_gemma":0.04368999,"domain_scores_codex":[0.9986146,0.0001421303,0.0004585749,0.0003650312,0.00006558171,0.0003541005],"domain_scores_gemma":[0.9991599,0.00009562628,0.0002571129,0.0003378727,0.0001004763,0.00004897609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001092794,0.0001953905,0.9671633,0.00001225541,0.0003747578,0.000005495701,0.0003159658,0.0001289819,0.03069693,0.00002685835,0.0002649252,0.0007058815],"study_design_scores_gemma":[0.0003951442,0.0003202204,0.9778166,0.00004990819,0.0002434386,0.00002416479,0.00004313657,0.00005979424,0.01999325,0.00001961404,0.0008135276,0.0002211368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981627,0.0001309208,0.0001154779,0.00005271706,0.0002353774,0.0004684212,0.00002444278,0.00004708659,0.0007628382],"genre_scores_gemma":[0.9982485,0.000007731583,0.0001750137,0.00003412564,0.00001540982,0.00008107794,0.0001336435,0.00001761537,0.00128689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01329005,"threshold_uncertainty_score":0.9999143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008815155138791723,"score_gpt":0.2954244678470349,"score_spread":0.2866093127082432,"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."}}