{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004442243,0.0002388948,0.0007328609,0.001129768,0.00003236944,0.00001545382,0.0002164812,0.0001850883,0.0003817083],"category_scores_gemma":[0.00006836163,0.0002106095,0.0001857469,0.002461468,0.00003608946,0.0001217984,0.00003568513,0.0001408685,0.00000263979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000525906,"about_ca_system_score_gemma":0.00005324064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005463322,"about_ca_topic_score_gemma":0.001561702,"domain_scores_codex":[0.9980302,0.0001043891,0.0006918616,0.0003677859,0.0003105437,0.0004952187],"domain_scores_gemma":[0.9990122,0.00008178882,0.0002676914,0.0004416978,0.00008653755,0.0001100663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002009775,0.003512101,0.3847236,0.0003254398,0.00631207,0.0004363499,0.003657624,0.02330342,0.3660509,0.05059833,0.01265938,0.146411],"study_design_scores_gemma":[0.002113063,0.0009089062,0.9276605,0.0001545344,0.0004105726,0.0000305526,0.0001128434,0.004527738,0.0347344,0.001411443,0.02709735,0.0008380627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8984156,0.004244125,0.0005222321,0.0000509708,0.0001384803,0.000109313,0.000005493826,0.00003247439,0.09648133],"genre_scores_gemma":[0.9971406,0.0002107396,0.0001473588,0.00006285104,0.0000251321,0.000004315856,0.000002874697,0.00001955037,0.002386555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5429369,"threshold_uncertainty_score":0.8588404,"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."}}