{"id":"W157837399","doi":"10.2166/wqrj.2003.006","title":"A Conceptual Model for Cryptosporidium Transport in Watersheds","year":2003,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Parasitic Infections and Diagnostics","field":"Immunology and Microbiology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confluence; Hydrology (agriculture); Environmental science; Tributary; Watershed; Surface runoff; Settling; SWAT model; Environmental engineering; Ecology; Geology; Geotechnical engineering; Computer science; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005788727,0.0006914354,0.0006179694,0.0007360633,0.0009164927,0.001919846,0.002201434,0.002023794,0.005002833],"category_scores_gemma":[0.00156389,0.0005264778,0.001050745,0.0008510185,0.001094299,0.002029304,0.0009786483,0.001221892,0.0004271633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003068996,"about_ca_system_score_gemma":0.002621633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03389291,"about_ca_topic_score_gemma":0.01200351,"domain_scores_codex":[0.9997155,0.00008770077,0.00001869624,0.00007733663,0.00006201279,0.00003878301],"domain_scores_gemma":[0.9995234,0.0002421913,0.0000448627,0.00002738307,0.0001206349,0.00004157178],"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":[0.00001805905,0.00002491615,0.000483301,0.00002733412,0.00000945795,0.00006643026,0.00005281226,0.9790064,0.000888499,0.01783645,0.0001460625,0.001440426],"study_design_scores_gemma":[0.00001460521,0.00001711336,0.00008872393,0.000004862164,0.000005832643,0.00001092374,0.0000239967,0.9959275,0.0001712384,0.002902053,0.0008274235,0.000005725637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1505599,0.0003168788,0.8304448,0.001301529,0.0001133366,0.0003119387,0.001569818,0.000661417,0.01472054],"genre_scores_gemma":[0.9046255,0.0004749504,0.08161106,0.0001248479,0.00003387211,0.0007187785,0.0007788243,0.0000959844,0.01153618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03389291,"threshold_uncertainty_score":0.06739122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1761948468936463,"score_gpt":0.4190562587902914,"score_spread":0.2428614118966451,"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."}}