{"id":"W4385068553","doi":"10.3390/w15142641","title":"Intensity–Duration–Frequency Curves for Dependent Datasets","year":2023,"lang":"en","type":"article","venue":"Water","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Precipitation; Multivariate statistics; Univariate; Range (aeronautics); Statistics; Generalized extreme value distribution; Duration (music); Maxima; Intensity (physics); Environmental science; Independence (probability theory); Extreme value theory; Mathematics; Climatology; Econometrics; Meteorology; Geography; Geology; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002265677,0.00005322591,0.00007210326,0.00002075814,0.0001009077,0.000009511044,0.0001128552,0.00003320499,0.002594759],"category_scores_gemma":[0.00002112807,0.0000351188,0.00003491565,0.0000761687,0.0000494394,0.0001482426,0.00009735687,0.00003514328,0.00726771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001658896,"about_ca_system_score_gemma":0.000001277768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001399033,"about_ca_topic_score_gemma":0.000320969,"domain_scores_codex":[0.9994434,0.00001561746,0.0001029985,0.0001687057,0.00008884897,0.0001804488],"domain_scores_gemma":[0.9997712,0.00001334164,0.00001289985,0.0001667251,0.00000340783,0.00003240569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003878788,0.00007060082,0.1040774,0.00004075477,0.00008999486,0.00006850195,0.0007219583,0.000898901,0.07640139,0.0001258954,0.8162571,0.001208728],"study_design_scores_gemma":[0.0017926,0.0003309884,0.1242756,0.0000581207,0.0005206352,0.00006881041,0.0001876829,0.02084156,0.2830572,0.0913551,0.4760625,0.001449112],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792815,0.00003617677,0.001125789,0.01200716,0.0002780115,0.0003181119,0.0001642951,0.0001556918,0.006633219],"genre_scores_gemma":[0.9941934,0.00002260221,0.0001772328,0.001454672,0.00002871451,0.0000315471,0.001230226,0.000005127573,0.002856496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3401946,"threshold_uncertainty_score":0.998317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686004010512766,"score_gpt":0.251025640871878,"score_spread":0.2341656007667504,"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."}}