{"id":"W1973146499","doi":"10.1016/j.envpol.2011.01.038","title":"BETR global – A geographically-explicit global-scale multimedia contaminant fate model","year":2011,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Per- and polyfluoroalkyl substances research","field":"Environmental Science","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Environmental science; Scale (ratio); Term (time); Grid; Pollutant; Implementation; Steady state (chemistry); Geography; Chemistry; Cartography; Software engineering","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":[0.0002538987,0.0006410858,0.0005891951,0.0004218173,0.000386939,0.0008733565,0.001900942,0.00155467,0.004232361],"category_scores_gemma":[0.0009939082,0.0004794087,0.0007494968,0.0006505114,0.0005342432,0.00137906,0.00110467,0.0007392731,0.0005834234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009919878,"about_ca_system_score_gemma":0.0009872208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04441557,"about_ca_topic_score_gemma":0.02664867,"domain_scores_codex":[0.9999127,0.00001923704,0.000005233329,0.00003086579,0.00001686246,0.00001505991],"domain_scores_gemma":[0.999726,0.000120529,0.00002597515,0.00004107376,0.00005268205,0.00003377064],"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":[0.00002402217,0.00002163287,0.0003747934,0.00001062571,0.00001646113,0.00002644778,0.00000735411,0.9949586,0.0004632293,0.001844084,0.0004242899,0.001828528],"study_design_scores_gemma":[0.00001331192,0.000006872355,0.00009244031,0.000001172279,0.000005220032,0.000004418664,0.000004465347,0.9981142,0.0001487142,0.001076293,0.0005287546,0.000004016151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5173039,0.0009748896,0.41407,0.001871595,0.0003246659,0.0002101729,0.01436104,0.004482069,0.04640161],"genre_scores_gemma":[0.923128,0.0004023663,0.06167146,0.0002527052,0.00006805595,0.0001486127,0.004675664,0.0003021951,0.009351003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04441557,"threshold_uncertainty_score":0.08831406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0155831216027005,"score_gpt":0.2314846041238054,"score_spread":0.2159014825211049,"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."}}