{"id":"W3125614888","doi":"10.22004/ag.econ.37044","title":"Wind Integration into Various Generation Mixtures","year":2007,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"University of Victoria","keywords":"Tonne; Environmental science; Wind power; Electricity generation; Range (aeronautics); Natural gas; Electric power system; Operating cost; Waste management; Engineering; Power (physics); Electrical engineering; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.001603504,0.000413965,0.0004509924,0.001111258,0.0001202648,0.0002670144,0.0004560707,0.001535696,0.00005520055],"category_scores_gemma":[0.0002425498,0.000460589,0.0001186528,0.0002385484,0.0001037252,0.0001803931,0.0002081554,0.002847347,0.00002117751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00290418,"about_ca_system_score_gemma":0.000246839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005469411,"about_ca_topic_score_gemma":0.003238119,"domain_scores_codex":[0.9973688,0.000198237,0.0008456605,0.0006638175,0.0002953172,0.0006281633],"domain_scores_gemma":[0.9985615,0.0001444537,0.0001110707,0.0007915464,0.0002547395,0.0001366753],"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":[0.00001436356,0.00002500327,0.00006110882,0.00009599659,0.00006597058,0.00001380193,0.0007689296,0.8823995,0.00378565,0.0003646812,0.0002437349,0.1121613],"study_design_scores_gemma":[0.0002702456,0.00003865382,0.0001598498,0.0002313348,0.000008768072,0.000009909478,0.0002273173,0.9825401,0.0102041,0.0007613904,0.005026415,0.000521971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6752449,0.001202525,0.01538784,0.0001606244,0.006719141,0.002242991,0.00005763611,0.0008529162,0.2981315],"genre_scores_gemma":[0.9865042,0.0041949,0.006023813,0.00003965557,0.0009831645,0.0001516378,0.0007886046,0.0001709982,0.001143054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3112593,"threshold_uncertainty_score":0.9997846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02014441933555697,"score_gpt":0.2780612095909689,"score_spread":0.2579167902554119,"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."}}