{"id":"W4392239955","doi":"10.3390/w16050707","title":"Dissolved Oxygen Forecasting for Lake Erie’s Central Basin Using Hybrid Long Short-Term Memory and Gated Recurrent Unit Networks","year":2024,"lang":"en","type":"article","venue":"Water","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakes Environmental (Canada); University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Water quality; Surface runoff; Freshwater ecosystem; Pollution; Stormwater; Hydrology (agriculture); Drainage basin; Ecosystem; Ecology; Cartography; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003733613,0.0002344096,0.0002114202,0.0000346099,0.0002492204,0.0001969843,0.0001464086,0.00008636284,0.0009274767],"category_scores_gemma":[0.00003236295,0.0001632753,0.00008346323,0.0001074821,0.0001915506,0.0002148445,0.0002625261,0.0002120533,0.00002542297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009907268,"about_ca_system_score_gemma":0.000006102876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003090411,"about_ca_topic_score_gemma":0.0003172643,"domain_scores_codex":[0.9981722,0.00005820855,0.0002800285,0.0005246917,0.0001713634,0.0007935237],"domain_scores_gemma":[0.999555,0.00006754731,0.00002509524,0.0001617261,0.000008091967,0.0001825374],"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":[0.0006987018,0.0003673518,0.1816279,0.0006325856,0.0003292676,0.001469733,0.005054368,0.3852223,0.05303334,0.00003162844,0.007676696,0.3638562],"study_design_scores_gemma":[0.0001976413,0.0001094887,0.005794682,0.0001729302,0.00007121719,0.0001227352,0.000008053115,0.9784223,0.003770578,0.0001583965,0.01081811,0.0003538702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913247,0.00007808016,0.006970935,0.000174498,0.0006082635,0.0003662734,0.00005268004,0.0001578994,0.000266653],"genre_scores_gemma":[0.9978778,0.000005387523,0.001294005,0.00009789116,0.0002023191,0.00001241143,0.0001711511,0.00004484407,0.0002941876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5932,"threshold_uncertainty_score":0.9999858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04635528877780506,"score_gpt":0.2589884338628197,"score_spread":0.2126331450850146,"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."}}