{"id":"W7054765348","doi":"","title":"Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions","year":2017,"lang":"en","type":"article","venue":"Figshare","topic":"Laser Design and Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Arable land; Calibration; Simulation modeling; Grassland; Greenhouse gas; Crop yield; Productivity; Temperate climate; Ensemble forecasting","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001731179,0.00005794171,0.00007709963,0.00002653251,0.0001336066,0.00008574584,0.00005763591,0.00003973921,0.0002373958],"category_scores_gemma":[0.0001721189,0.00005447859,0.000008379609,0.00003139062,0.00001017745,0.0002698205,0.00004034206,0.00007199246,0.000001849885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008066077,"about_ca_system_score_gemma":0.00001600961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008749927,"about_ca_topic_score_gemma":0.00003731149,"domain_scores_codex":[0.9997195,0.000004764527,0.00006935139,0.00009516143,0.00003873455,0.00007248967],"domain_scores_gemma":[0.9996855,0.00003577744,0.00002708466,0.0001939998,0.00002736123,0.00003028564],"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":[0.000005869919,0.0001083016,0.007397984,0.001388066,0.00003926014,0.000004258353,0.00239759,0.7956004,0.09961592,0.0003974307,0.07240985,0.02063508],"study_design_scores_gemma":[0.0001776554,0.000003744972,0.05738074,0.0005957373,0.000006706875,0.000001460167,0.00004949627,0.9314899,0.007028556,0.001175099,0.001947362,0.0001435212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9661655,0.0005178768,0.0006727345,0.000388347,0.00002176768,0.0004097466,0.02760863,0.0001175894,0.004097853],"genre_scores_gemma":[0.9986389,0.000002419548,0.0004340281,0.000002979906,0.00001659299,0.00002630287,0.0007425079,0.000008425076,0.0001278594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1358895,"threshold_uncertainty_score":0.2599317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06805363358962374,"score_gpt":0.3007367940136579,"score_spread":0.2326831604240342,"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."}}