{"id":"W1973642385","doi":"10.1002/env.483","title":"The bivariate lognormal distribution for describing joint statistical properties of a multivariate storm event","year":2002,"lang":"en","type":"article","venue":"Environmetrics","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Joint probability distribution; Log-normal distribution; Storm; Bivariate analysis; Marginal distribution; Multivariate statistics; Event (particle physics); Statistics; Mathematics; Conditional probability distribution; Copula (linguistics); Joint (building); Multivariate normal distribution; Econometrics; Meteorology; Geography; 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":[0.0006452112,0.0001258386,0.0001749795,0.00003812356,0.0003770118,0.00001738713,0.0001804554,0.00008726702,0.0004733432],"category_scores_gemma":[0.0006775711,0.0000843601,0.0001000103,0.0003411477,0.0003789946,0.0001185979,0.0001396778,0.0001274586,0.0001263435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149964,"about_ca_system_score_gemma":0.000003005034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000209879,"about_ca_topic_score_gemma":0.00004545263,"domain_scores_codex":[0.9987221,0.0001000407,0.0003431393,0.0002360323,0.000271172,0.0003275337],"domain_scores_gemma":[0.9993151,0.000221961,0.0001463405,0.0002374639,0.000005688029,0.00007347805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008335759,0.004174977,0.2031279,0.0001581318,0.0009984614,0.00004780186,0.006099978,0.2098359,0.1123703,0.02123742,0.01992725,0.4211883],"study_design_scores_gemma":[0.001736503,0.000478646,0.1792464,0.00002302458,0.0004039226,0.00001330204,0.0001743515,0.7090909,0.02063454,0.001341433,0.08618,0.0006769736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5109507,0.0004191861,0.4875703,0.0003519881,0.00009263618,0.0003173779,0.00006916241,0.00002006323,0.0002086203],"genre_scores_gemma":[0.997299,0.0001180439,0.002030555,0.00002988488,0.00002632227,0.000034813,0.00001953506,0.00001008745,0.0004317481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.499255,"threshold_uncertainty_score":0.5182776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04754101843449469,"score_gpt":0.2220100953289229,"score_spread":0.1744690768944281,"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."}}