{"id":"W1989687941","doi":"10.1139/l09-027","title":"Characterization of 1-h rainfall temporal patterns using a Kohonen neural network: a Québec City case study","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Storm; Range (aeronautics); Self-organizing map; Rain gauge; Environmental science; Meteorology; Cluster analysis; Intensity (physics); Artificial neural network; Geography; Computer science; Artificial intelligence; Engineering; Precipitation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003277971,0.0004266268,0.0002307161,0.0009605418,0.0006828721,0.0006519945,0.000906178,0.0006302717,0.001564492],"category_scores_gemma":[0.001244054,0.0001886319,0.0002816063,0.001820912,0.0003851178,0.0003204385,0.0002420285,0.0003137091,0.0001171454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007938636,"about_ca_system_score_gemma":0.002407714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9372248,"about_ca_topic_score_gemma":0.9519539,"domain_scores_codex":[0.9998397,0.00002498974,0.000008096085,0.00003661845,0.00004238143,0.00004811403],"domain_scores_gemma":[0.9994158,0.000224905,0.00004986031,0.00003895027,0.0002192011,0.0000512637],"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":[0.0005117956,0.0004937663,0.2790785,0.0002095543,0.0002109356,0.00461245,0.0009671746,0.6361094,0.006418728,0.002365287,0.006313975,0.06270849],"study_design_scores_gemma":[0.00004581549,0.0000703655,0.1326096,0.00001704477,0.00004245937,0.0001639546,0.0009325476,0.8631516,0.001123396,0.0002994644,0.001505778,0.00003799723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928201,0.00009247888,0.003021344,0.00016915,0.000004281697,0.00006598335,0.001668248,0.00007407623,0.002084302],"genre_scores_gemma":[0.995091,0.00006989736,0.002574057,0.00001506749,0.000002173484,0.00002098946,0.0009478959,0.000007617175,0.001271469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06277519,"threshold_uncertainty_score":0.1262897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02114754983720648,"score_gpt":0.2123159043904544,"score_spread":0.1911683545532479,"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."}}