{"id":"W3203924145","doi":"10.3390/w13192688","title":"A Probabilistic Model for Maximum Rainfall Frequency Analysis","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Instytut Meteorologii i Gospodarki Wodnej – Państwowy Instytut Badawczy","keywords":"Statistics; Mathematics; Autocorrelation; Spearman's rank correlation coefficient; Precipitation; Probability density function; Random variable; Correlation coefficient; Context (archaeology); Meteorology; Physics","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":[0.0002148095,0.00008664397,0.0001683637,0.00003338483,0.0000999465,0.00001851425,0.0001136736,0.0000690388,0.003901112],"category_scores_gemma":[0.00003101331,0.00005994486,0.0002098151,0.0002452952,0.00007522998,0.00009220715,0.0000795495,0.00004966067,0.0005736281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004289633,"about_ca_system_score_gemma":0.000006799634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008338339,"about_ca_topic_score_gemma":0.001197049,"domain_scores_codex":[0.9991392,0.00003786807,0.0001470053,0.0003096486,0.0001033938,0.0002628187],"domain_scores_gemma":[0.9996208,0.00002146523,0.00001756858,0.0002717542,0.00001124743,0.00005713978],"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":[0.00003702707,0.0002878924,0.0937867,0.00002351294,0.001155822,0.0000664947,0.003292992,0.868504,0.02735942,0.0007996046,0.003522846,0.001163683],"study_design_scores_gemma":[0.0002124279,0.00001396703,0.001317049,7.387323e-7,0.0008906504,0.000002672017,0.00001064765,0.8894178,0.003062783,0.1030837,0.001815444,0.0001721759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.849808,0.00002348386,0.1363639,0.002133309,0.00003941576,0.0001579716,0.00001801107,0.00006670946,0.01138915],"genre_scores_gemma":[0.9853279,0.000001666756,0.006093521,0.0006255266,0.00001588044,0.00004898999,0.00007257975,0.000009027793,0.007804895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1355199,"threshold_uncertainty_score":0.9970095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297613592388412,"score_gpt":0.2278532443724046,"score_spread":0.2148771084485205,"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."}}