{"id":"W2383768674","doi":"","title":"Analysis and Forecast of Hubei Power Market in Spring of 2009","year":2009,"lang":"en","type":"article","venue":"Hubei Electric Power","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Supply and demand; Spring (device); Mains electricity; Electricity demand; Electricity; Electricity market; Power (physics); Environmental science; Economics; Business; Natural resource economics; Environmental economics; Engineering; Electricity generation; Electrical engineering; Geography; Microeconomics; Mechanical 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":[0.0002670563,0.0003279965,0.0002937241,0.001134738,0.0002735883,0.0006347833,0.0003191354,0.0004269882,0.001860901],"category_scores_gemma":[0.000769371,0.0001928026,0.0002364469,0.001121106,0.0001054531,0.0007911752,0.0001418147,0.0005532251,0.0004128298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001388672,"about_ca_system_score_gemma":0.000427854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08116654,"about_ca_topic_score_gemma":0.09383665,"domain_scores_codex":[0.9999027,0.000008100025,0.000005917645,0.00002032105,0.00004393146,0.00001885866],"domain_scores_gemma":[0.9996355,0.00006429054,0.0000570082,0.00001275814,0.0002020436,0.00002854808],"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":[0.001382864,0.0002617939,0.363646,0.0003111926,0.0002221173,0.002458241,0.0007205106,0.4664995,0.01696721,0.01533313,0.07753499,0.05466242],"study_design_scores_gemma":[0.00003427495,0.00008951791,0.2554577,0.00002145858,0.00004171037,0.0001097025,0.0005387147,0.7286159,0.003435345,0.001673271,0.009926223,0.00005612379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694325,0.0003471129,0.005452056,0.0009734759,0.000120777,0.00003346028,0.01438498,0.0003447119,0.00891087],"genre_scores_gemma":[0.9867831,0.0002684578,0.001452918,0.00004986519,0.00003371767,0.00001626687,0.008371345,0.00002032555,0.003003911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08116654,"threshold_uncertainty_score":0.1613882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004488980202190671,"score_gpt":0.2039625485170164,"score_spread":0.1994735683148257,"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."}}