{"id":"W2149284344","doi":"10.1371/journal.pntd.0004028","title":"Ecological Model to Predict Potential Habitats of Oncomelania hupensis, the Intermediate Host of Schistosoma japonicum in the Mountainous Regions, China","year":2015,"lang":"en","type":"article","venue":"PLoS neglected tropical diseases","topic":"Parasites and Host Interactions","field":"Immunology and Microbiology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Oncomelania hupensis; Oncomelania; Normalized Difference Vegetation Index; Schistosoma japonicum; Intermediate host; Geography; Snail; SCHISTOSOMIASIS JAPONICA; Schistosomiasis; Habitat; China; Ecology; Digital elevation model; Diameter at breast height; Physical geography; Host (biology); Forestry; Biology; Remote sensing; Helminths; Climate change","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000358843,0.0007447617,0.0004497892,0.0009152658,0.0004052691,0.0006550751,0.0007317955,0.0006283122,0.001723498],"category_scores_gemma":[0.0006059184,0.0002711262,0.0005852501,0.0004762457,0.0002278197,0.0004235548,0.0005192677,0.0002988583,0.0001904131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001030871,"about_ca_system_score_gemma":0.001436603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06469726,"about_ca_topic_score_gemma":0.0342547,"domain_scores_codex":[0.9999045,0.00002204696,0.000006614787,0.00002988275,0.00001114768,0.00002577213],"domain_scores_gemma":[0.9998195,0.00007111558,0.00002477886,0.000007754411,0.00004760425,0.00002941045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005276618,0.00007469672,0.02791422,0.0000357896,0.0000419268,0.0001030093,0.00003493764,0.9655161,0.0005273399,0.0002398355,0.0004241415,0.005035102],"study_design_scores_gemma":[0.000006666448,0.00001467687,0.002368019,0.000002343073,0.000006876044,0.00001004459,0.00002044157,0.9973632,0.00003219473,0.0001007628,0.0000725074,0.000002359024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654935,0.0002419226,0.02924918,0.0002778008,0.00002919732,0.00006587201,0.001025895,0.0003963028,0.003220351],"genre_scores_gemma":[0.9953688,0.00007699906,0.003160414,0.00002289385,0.000005128903,0.00005515074,0.0004994647,0.00001030007,0.0008009343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06469726,"threshold_uncertainty_score":0.1286414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0214845313142329,"score_gpt":0.2674594490358216,"score_spread":0.2459749177215887,"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."}}