{"id":"W4391847743","doi":"10.1016/j.jhydrol.2024.130911","title":"Bayesian analysis of variance for quantifying multi-factor effects on drought propagation","year":2024,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"National Key Research and Development Program of China; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Bayesian probability; Variance (accounting); Statistics; Environmental science; Econometrics; Mathematics; Economics","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":[0.0006253688,0.0001267813,0.0004919483,0.0004089835,0.00006864462,0.00001365226,0.0001986451,0.0001485547,0.0004361913],"category_scores_gemma":[0.000168187,0.00009619341,0.0004247174,0.0008378518,0.000103743,0.0001947556,0.00002904574,0.0002153709,0.00003319875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000771065,"about_ca_system_score_gemma":0.00002023239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002311179,"about_ca_topic_score_gemma":0.0001208864,"domain_scores_codex":[0.9986925,0.0001641239,0.0005028535,0.0002276515,0.0002010011,0.0002119129],"domain_scores_gemma":[0.9988873,0.0005399192,0.0003245008,0.0001596209,0.00002116448,0.00006752215],"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":[0.001724072,0.001065237,0.2279609,0.0004280907,0.01311283,0.0006129082,0.003756718,0.4700862,0.2291511,0.002348964,0.001950392,0.04780259],"study_design_scores_gemma":[0.0007423986,0.001208352,0.04118797,0.0000466502,0.003114062,0.00004334313,0.00001079498,0.9336925,0.01562144,0.001157765,0.002985394,0.0001893177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8065228,0.0002684547,0.1915682,0.0008971635,0.0003812298,0.000131774,0.000007367193,0.00001273709,0.00021026],"genre_scores_gemma":[0.9962984,0.00002846618,0.003201562,0.0002157433,0.00009562767,0.000006169234,0.000004332466,0.00001083616,0.0001388337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4636063,"threshold_uncertainty_score":0.4775988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962821828945479,"score_gpt":0.2960723259016442,"score_spread":0.2764441076121894,"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."}}