{"id":"W1531401350","doi":"10.1029/2010wr010266","title":"Two‐component mixtures of normal, gamma, and Gumbel distributions for hydrological applications","year":2011,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Gumbel distribution; Independent and identically distributed random variables; Marginal distribution; Skewness; Gamma distribution; Mathematics; Mixture model; Applied mathematics; Generalized gamma distribution; Bayesian probability; Computer science; Statistical physics; Statistics; Random variable; Extreme value theory","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008151786,0.00007980202,0.0001388359,0.00006797363,0.0003794611,0.00001323597,0.0002987796,0.00008104431,0.001516997],"category_scores_gemma":[0.00002389805,0.00005206201,0.000062812,0.0001706065,0.0009672317,0.00005857335,0.0003735708,0.0001690082,0.0001592832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002231947,"about_ca_system_score_gemma":0.000002187403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008268165,"about_ca_topic_score_gemma":0.0001355788,"domain_scores_codex":[0.9987223,0.0001511109,0.0001855026,0.0002868903,0.000247171,0.0004070605],"domain_scores_gemma":[0.9994734,0.0001026177,0.00002445798,0.0002621326,0.00002213503,0.000115277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001230003,0.002187009,0.6005284,0.0001287436,0.0003641583,0.00003064237,0.01874054,0.0008350729,0.3510323,0.005633015,0.005858829,0.01343124],"study_design_scores_gemma":[0.00201398,0.00105825,0.1241435,0.00001451292,0.0001617586,0.0000406439,0.0004382435,0.008446637,0.3004001,0.05832679,0.5043262,0.0006294432],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862586,0.0000876909,0.002171332,0.0003446674,0.000005152406,0.000335509,0.00002783527,0.00001492153,0.01075434],"genre_scores_gemma":[0.9979376,0.0000200705,0.001006916,0.0000261458,0.0000281397,0.000251196,0.00003601656,0.000005650528,0.0006882784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4984673,"threshold_uncertainty_score":0.9993957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04875114676246468,"score_gpt":0.3113785347523568,"score_spread":0.2626273879898921,"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."}}