{"id":"W3199011366","doi":"10.1109/icisce50968.2020.00049","title":"Air Temperature Forecasting using Traditional and Deep Learning Algorithms","year":2020,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Toronto","funders":"","keywords":"Mean squared error; Machine learning; Artificial intelligence; Computer science; Air temperature; Deep learning; Algorithm; Atmospheric model; Meteorology; Mathematics; Statistics","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":[0.00004709401,0.0001310028,0.0001178392,0.00003035948,0.0001469946,0.00003970404,0.00004570725,0.00006933072,0.00007864608],"category_scores_gemma":[0.00003000866,0.000127342,0.00003237933,0.0001394139,0.00001773108,0.0001632375,0.00001366207,0.0002728112,0.000003187105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001502085,"about_ca_system_score_gemma":0.00000573015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004343089,"about_ca_topic_score_gemma":0.000002473711,"domain_scores_codex":[0.9994227,0.00001100291,0.000131687,0.0001440221,0.00009530477,0.000195278],"domain_scores_gemma":[0.9997624,0.0000506005,0.00001457684,0.00003253446,0.00001534083,0.0001245136],"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":[0.000005497557,0.000006929603,0.001057335,0.0001298395,0.00006046187,0.00004656026,0.001786627,0.9206566,0.0351755,0.0009913604,0.0001814251,0.0399019],"study_design_scores_gemma":[0.0001652224,0.00003033199,0.0001621284,0.00003193258,0.000008669245,0.00006981044,0.0001998335,0.9936702,0.003737088,0.00004643649,0.001698915,0.000179423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960342,0.0008489201,0.02298983,0.0001498794,0.0002673376,0.00006370548,0.000005834057,0.0007248201,0.01460768],"genre_scores_gemma":[0.9821585,0.0000184115,0.01707412,0.0001870588,0.0004777894,0.000001836497,0.00001639122,0.00003297638,0.00003293819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07301365,"threshold_uncertainty_score":0.5192855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03766111911098595,"score_gpt":0.2017424672401741,"score_spread":0.1640813481291881,"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."}}