{"id":"W4394847051","doi":"10.5194/gmd-17-2877-2024","title":"HydroFATE (v1): a high-resolution contaminant fate model for the global river system","year":2024,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Effluent; Surface water; Contamination; Aquatic ecosystem; Groundwater; Wastewater; Surface runoff; Sewage treatment; Population; Ecosystem; STREAMS; Environmental chemistry; Environmental engineering; Hydrology (agriculture); Ecology; Biology; Chemistry; Computer science","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":[0.0002845364,0.0008960155,0.0006067022,0.0004476605,0.0004971085,0.001064208,0.00119452,0.00168616,0.004861356],"category_scores_gemma":[0.0009121539,0.0004502613,0.00107964,0.0006160769,0.0004624896,0.0006990656,0.0008293786,0.0008751683,0.0005644726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230746,"about_ca_system_score_gemma":0.001080172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03793515,"about_ca_topic_score_gemma":0.01965911,"domain_scores_codex":[0.999867,0.0000431448,0.000007144822,0.00003802638,0.00002313665,0.00002152537],"domain_scores_gemma":[0.9996452,0.0001968496,0.00003564589,0.00002532875,0.00006923646,0.00002773741],"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":[0.00002503915,0.0000122679,0.0008893728,0.00002454918,0.0000122128,0.00004009262,0.00001209323,0.9967361,0.0004276346,0.000622314,0.0002859028,0.0009123681],"study_design_scores_gemma":[0.00002733572,0.00002240826,0.0003616861,0.000004502329,0.00000620393,0.00001140716,0.00001160925,0.9977636,0.0002405402,0.0003968416,0.001147176,0.000006611107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8026485,0.0008732901,0.1272713,0.001024562,0.0001350797,0.0004546636,0.03144453,0.003163656,0.0329844],"genre_scores_gemma":[0.9559237,0.0003966162,0.02869097,0.0001195127,0.00002415078,0.0004993276,0.00718396,0.0002490772,0.006912599],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03793515,"threshold_uncertainty_score":0.07542866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03123921498586469,"score_gpt":0.2601970342754619,"score_spread":0.2289578192895972,"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."}}