{"id":"W4239540229","doi":"10.5194/amt-2021-106","title":"Field Testing Two Flux Footprint Models","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Footprint; Flux (metallurgy); Dispersion (optics); Environmental science; Field (mathematics); Atmospheric sciences; Lagrangian; Mechanics; Meteorology; Physics; Mathematics; Geology; Materials science; Applied mathematics; Optics","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":[0.001546194,0.0005660211,0.0004925942,0.0004982266,0.0003023761,0.0005895554,0.001189864,0.0009491452,0.001689031],"category_scores_gemma":[0.003470732,0.0002454303,0.0004352478,0.0004127066,0.0002778156,0.001335675,0.0004279769,0.0004393953,0.0001995445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130746,"about_ca_system_score_gemma":0.0006238465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02080437,"about_ca_topic_score_gemma":0.008250291,"domain_scores_codex":[0.9995969,0.00009339275,0.00002362589,0.0001317344,0.0001160618,0.0000382887],"domain_scores_gemma":[0.9971992,0.001940418,0.0001247625,0.0002274495,0.0004305926,0.00007755787],"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":[0.0006007678,0.0004909519,0.01646454,0.00014081,0.00005880098,0.0000997925,0.0001547681,0.9263143,0.008975192,0.002696942,0.0006690529,0.04333412],"study_design_scores_gemma":[0.00003237616,0.0001221259,0.001446323,0.00000550396,0.000006295691,0.00001656425,0.00002434084,0.9947135,0.002985086,0.0003503083,0.0002868592,0.00001076292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8700114,0.0001369623,0.1236254,0.0001775825,0.00005577095,0.000141112,0.0007397797,0.001134664,0.003977257],"genre_scores_gemma":[0.9724188,0.00005154743,0.02619382,0.00002675008,0.000005610947,0.00009961788,0.0003550236,0.00004409565,0.0008046875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02080437,"threshold_uncertainty_score":0.04136658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06306125419400752,"score_gpt":0.2815341174889983,"score_spread":0.2184728632949907,"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."}}