{"id":"W2786165902","doi":"10.1109/pesgm.2017.8274667","title":"A novel decomposition-based localized short-term tidal current speed and direction prediction model","year":2017,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Predictability; Autoregressive integrated moving average; Hilbert–Huang transform; Time series; Computer science; Term (time); Autoregressive model; Long-term prediction; Tidal power; Series (stratigraphy); Volatility (finance); Current (fluid); Energy (signal processing); Algorithm; Mathematics; Engineering; Geology; Statistics; Machine learning; Econometrics","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":[],"consensus_categories":[],"category_scores_codex":[0.00006140789,0.0001176569,0.0001030474,0.00005083949,0.000212048,0.0001074185,0.0000660631,0.00005334684,0.00001450665],"category_scores_gemma":[0.000007840566,0.00011346,0.00003596966,0.00002078393,0.00002800474,0.0001892595,0.0000176291,0.00009422978,0.000002488305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003635268,"about_ca_system_score_gemma":0.000009207534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002612468,"about_ca_topic_score_gemma":0.00005077872,"domain_scores_codex":[0.9994861,0.000003837921,0.0001381685,0.0001388686,0.00009063949,0.0001424123],"domain_scores_gemma":[0.9996966,0.00001417038,0.00002104793,0.0001735664,0.00002217114,0.00007245981],"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":[0.00003210537,0.00006604853,0.01046019,0.00009798295,0.00003444959,0.000001384405,0.00008576801,0.8716018,0.07033855,0.0003902112,0.0002869993,0.04660454],"study_design_scores_gemma":[0.0004406782,0.00001440212,0.005420815,0.00007338604,0.00001700252,0.0000050001,0.000001688228,0.9856741,0.007922063,0.00003147779,0.0002772697,0.0001221371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5119364,0.00009333653,0.4769383,0.00002133647,0.0007141734,0.0000822721,0.00002272413,0.0003801297,0.009811242],"genre_scores_gemma":[0.9971535,0.00002863836,0.002559493,0.000007399292,0.0001289076,0.000006909191,0.00003374714,0.0000195326,0.00006189317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.485217,"threshold_uncertainty_score":0.4626764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418151292326778,"score_gpt":0.267646310467673,"score_spread":0.2434647975444052,"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."}}