{"id":"W4378226867","doi":"10.22541/essoar.168500283.32887682/v1","title":"Modeling denitrification: can we report what we don’t know?","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst; European Commission","keywords":"Biogeochemical cycle; Denitrification; Limiting; Environmental science; NOx; Field (mathematics); Nitrogen; Computer science; Environmental resource management; Atmospheric sciences; Environmental chemistry; Engineering; Chemistry; Mathematics; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02674093,0.002035368,0.003498852,0.002519362,0.001666124,0.009288917,0.00503598,0.006894939,0.01102582],"category_scores_gemma":[0.1439487,0.0009520325,0.002285334,0.002377577,0.004538249,0.03173155,0.004563448,0.0110824,0.007083444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003072751,"about_ca_system_score_gemma":0.007241758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009039502,"about_ca_topic_score_gemma":0.005679945,"domain_scores_codex":[0.9907197,0.00390763,0.001032766,0.001172296,0.00260239,0.0005651464],"domain_scores_gemma":[0.9154449,0.04136639,0.005768365,0.007786889,0.02426003,0.005373432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005424684,0.0002845517,0.005354745,0.01119959,0.001085036,0.0002485319,0.0008766455,0.004485239,0.001234589,0.03904633,0.4619679,0.4736743],"study_design_scores_gemma":[0.0001240179,0.0002324015,0.002522722,0.01675872,0.0006121551,0.000359852,0.002128334,0.005268691,0.001878866,0.3044481,0.6653363,0.0003299099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.004527495,0.5083691,0.0211614,0.4124252,0.04081544,0.00007952929,0.001550444,0.0009963101,0.01007508],"genre_scores_gemma":[0.09223241,0.6477743,0.03912016,0.1655453,0.03980591,0.0003824918,0.003173639,0.001668522,0.01029732],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02674093,"threshold_uncertainty_score":0.1414212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04064263295279613,"score_gpt":0.2576572893514237,"score_spread":0.2170146563986275,"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."}}