{"id":"W2127802901","doi":"10.1109/pes.2011.6038897","title":"Accommodating large amounts of variable generation in North America","year":2011,"lang":"en","type":"article","venue":"","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council","keywords":"Renewable energy; Wind power; Electricity generation; Fossil fuel; Environmental science; Coal; Environmental economics; Variable renewable energy; Electricity; Nameplate capacity; Natural gas; Non-renewable resource; Variable (mathematics); Natural resource economics; Electric power system; Business; Engineering; Waste management; Economics; Power (physics); Electrical 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":[0.00006698357,0.00006952311,0.0001039648,0.00009056884,0.00001270796,0.000005416848,0.00006458726,0.00004543335,0.0002856288],"category_scores_gemma":[0.00001403098,0.00006733774,0.00001115923,0.0003340039,0.000004775873,0.0001670306,0.000009597551,0.00005704251,0.0000147143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003863922,"about_ca_system_score_gemma":0.000007927699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001037497,"about_ca_topic_score_gemma":0.001627247,"domain_scores_codex":[0.9995036,0.0000176796,0.0002248165,0.00007100627,0.00005744423,0.0001254578],"domain_scores_gemma":[0.9997825,0.000005623435,0.00003112559,0.0001198496,0.00004535823,0.00001554211],"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":[0.00000198599,0.00003103486,0.01031454,0.00002328963,0.00001525614,7.662998e-7,0.0009616287,0.9805672,0.004259658,0.002886536,0.0003655113,0.0005726081],"study_design_scores_gemma":[0.0001351156,0.000009973574,0.001779137,0.000008819109,0.000002642352,4.96205e-7,0.0001284777,0.9878527,0.009669612,0.000008633911,0.0003184947,0.00008587599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5304796,0.00002477834,0.357694,0.000001158221,0.0002023796,0.000102006,0.000009182334,0.0001552961,0.1113316],"genre_scores_gemma":[0.9689933,0.000006292616,0.03075033,0.00001420012,0.00002468738,0.00001229779,0.00007745654,0.00001657164,0.0001048664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4385137,"threshold_uncertainty_score":0.3127435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581427586359259,"score_gpt":0.1861898586804485,"score_spread":0.1703755828168559,"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."}}