{"id":"W4395010606","doi":"10.3390/su16083461","title":"Advancing Spatial Drought Forecasts by Integrating an Improved Outlier Robust Extreme Learning Machine with Gridded Data: A Case Study of the Lower Mainland Basin, British Columbia, Canada","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université Laval","funders":"","keywords":"Outlier; Extreme learning machine; Mainland; Structural basin; Climatology; Data mining; Computer science; Meteorology; Artificial intelligence; Geography; Machine learning; Cartography; Geology; Geomorphology; Archaeology; Artificial neural network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0005706215,0.0006504038,0.0003795121,0.0006415286,0.0008292292,0.001050558,0.0009939934,0.0004376954,0.0005045963],"category_scores_gemma":[0.001746745,0.0001841273,0.0003128377,0.00166689,0.0003817416,0.0003240445,0.0004694907,0.0004475901,0.00006908619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00729984,"about_ca_system_score_gemma":0.00551028,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9511548,"about_ca_topic_score_gemma":0.9548048,"domain_scores_codex":[0.999781,0.00004897928,0.00001410788,0.00005197227,0.00004670334,0.00005737317],"domain_scores_gemma":[0.9995702,0.0001410657,0.00002960542,0.00003227241,0.000186237,0.00004064353],"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":[0.0002281069,0.0002181048,0.1236106,0.0001349414,0.000146899,0.001149983,0.0002612238,0.8221427,0.001618064,0.0008454923,0.0029419,0.046702],"study_design_scores_gemma":[0.0000224401,0.00002327789,0.03516729,0.00001489066,0.00003500435,0.00002836483,0.0004439167,0.9622946,0.0006784652,0.0002457525,0.001025319,0.00002071508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932672,0.0002380825,0.003350066,0.0003539646,0.0000121431,0.00004666354,0.00103849,0.0001667501,0.001526789],"genre_scores_gemma":[0.9945818,0.0001376956,0.00356911,0.0000257603,0.000005134568,0.00001412661,0.0008585689,0.0000113512,0.0007964522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04884517,"threshold_uncertainty_score":0.09826559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01024035741649711,"score_gpt":0.2226530991125721,"score_spread":0.212412741696075,"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."}}