{"id":"W1971257053","doi":"10.1016/j.meegid.2009.06.006","title":"ISSR, an effective molecular approach for studying genetic variability among Schistosoma japonicum isolates from different provinces in mainland China","year":2009,"lang":"en","type":"article","venue":"Infection Genetics and Evolution","topic":"Parasites and Host Interactions","field":"Immunology and Microbiology","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of British Columbia","keywords":"Schistosoma japonicum; UPGMA; Biology; Mainland China; Genetic diversity; China; Population; Genetic variation; Veterinary medicine; Geography; Zoology; Genetics; Demography; Gene; Schistosomiasis; Helminths","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":[],"consensus_categories":[],"category_scores_codex":[0.0001556767,0.0001730634,0.0002109219,0.0001169045,0.0002365002,0.00003642401,0.0000551349,0.0001939296,0.00001165708],"category_scores_gemma":[0.00003650383,0.0001583964,0.0000612933,0.0000766615,0.00007185284,0.0000984587,0.00002226451,0.0001911202,0.000002476054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001399647,"about_ca_system_score_gemma":0.00001545787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241263,"about_ca_topic_score_gemma":0.0003235051,"domain_scores_codex":[0.9988596,0.000249415,0.0002379679,0.000395667,0.00002583393,0.0002315296],"domain_scores_gemma":[0.9995834,0.00007246256,0.00009680554,0.0001704234,0.00004653856,0.00003037841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001517672,0.0006194151,0.7673145,0.00001542735,0.00007243818,3.800067e-7,0.0004003297,0.001374968,0.2205641,0.0003027091,0.000009232057,0.009174747],"study_design_scores_gemma":[0.0009153967,0.0006927307,0.9777152,0.00001801361,0.00006643905,0.00000929311,0.00004060275,0.0120938,0.00476121,0.003464296,0.00004576021,0.0001772484],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.911896,0.001129727,0.08571576,0.00001914366,0.0002411374,0.0008002119,0.00002522623,0.00003725589,0.0001355729],"genre_scores_gemma":[0.9989444,0.0000542039,0.0006787595,0.00001390582,0.00004189057,0.0001182287,0.0001176642,0.000009231387,0.00002169069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2158029,"threshold_uncertainty_score":0.6459219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006021593270063059,"score_gpt":0.245625286904456,"score_spread":0.2396036936343929,"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."}}