{"id":"W3081106270","doi":"","title":"Variogram-based global sensitivity analysis of environmental models with dependent variables","year":2018,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Variogram; Sensitivity (control systems); Environmental science; Econometrics; Statistics; Mathematics; Kriging; Engineering","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":[0.003295434,0.000218557,0.000478463,0.0002450511,0.0001365591,0.0001017188,0.0003482065,0.0001186305,0.0000185746],"category_scores_gemma":[0.0008345242,0.0001580479,0.000153928,0.0010871,0.0002630847,0.0001747324,0.00007694955,0.0001126807,0.00003480474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009341772,"about_ca_system_score_gemma":0.00009827514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00316559,"about_ca_topic_score_gemma":0.003322816,"domain_scores_codex":[0.9969262,0.0001700826,0.0006434528,0.0005883227,0.001311147,0.0003608249],"domain_scores_gemma":[0.9973429,0.001302171,0.0003827138,0.0006445164,0.0001586834,0.0001689473],"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":[0.00005948004,0.0001569755,0.04688253,0.000004219858,0.0002584245,0.00003143878,0.00008614199,0.95044,0.0006091168,0.0003150469,0.00004171563,0.00111487],"study_design_scores_gemma":[0.0004069984,0.000178874,0.256971,0.00005033875,0.0006757007,0.00001161486,0.000141702,0.7376915,0.0008436241,0.002664347,0.00005105432,0.0003133226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7023942,0.00002700488,0.2924002,0.0000281949,0.00008643631,0.0001022384,0.00008846908,0.00005033904,0.004822872],"genre_scores_gemma":[0.9671637,0.000001384751,0.0326673,0.00005266999,0.0000465097,0.000003394575,0.00001074685,0.00001066048,0.00004365641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2647694,"threshold_uncertainty_score":0.6445004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03751799879305191,"score_gpt":0.2714385415369199,"score_spread":0.233920542743868,"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."}}