{"id":"W2160123863","doi":"10.1109/icset.2008.4747199","title":"Forecasting spot electricity market prices using time series models","year":2008,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity market; Electricity; Volatility (finance); Spot contract; Econometrics; Electricity price forecasting; Spot market; Time series; Series (stratigraphy); Economics; Financial economics; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005097701,0.0004905985,0.0004793808,0.000615047,0.0001789153,0.0008030204,0.0005677836,0.0005377305,0.001063563],"category_scores_gemma":[0.001983951,0.0002963541,0.0004173538,0.0008624583,0.0001659172,0.0009797912,0.0001871009,0.0005133088,0.0002756933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004691641,"about_ca_system_score_gemma":0.0004088838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02120051,"about_ca_topic_score_gemma":0.01918745,"domain_scores_codex":[0.9997995,0.00006105511,0.00001360019,0.00004100762,0.0000665542,0.00001834193],"domain_scores_gemma":[0.9994886,0.0003358591,0.00007058334,0.00002460177,0.00006816503,0.00001219235],"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":[0.00003673473,0.00003233276,0.002091809,0.00002186338,0.0000438096,0.00003653297,0.00001765088,0.9751543,0.0006740857,0.001618177,0.0003178903,0.01995478],"study_design_scores_gemma":[0.000001348046,0.000003457306,0.0002150746,5.244986e-7,0.000001896329,0.000002096592,0.000001297791,0.9993423,0.00007809725,0.0002965358,0.00005613713,0.000001234961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.602123,0.0007566292,0.3895791,0.0003275579,0.0001163326,0.00005027798,0.0005654088,0.001066441,0.00541517],"genre_scores_gemma":[0.9775044,0.0003995509,0.01937737,0.00001876668,0.00004251808,0.00002999505,0.0004767772,0.00002459043,0.002126135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02120051,"threshold_uncertainty_score":0.04215419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0299094107181056,"score_gpt":0.1953100877397431,"score_spread":0.1654006770216375,"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."}}