{"id":"W4376874607","doi":"10.1016/j.energy.2023.127836","title":"The role of emerging technologies in Canada's electricity system transition","year":2023,"lang":"en","type":"article","venue":"Energy","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Mitacs","keywords":"Electricity; Electricity system; Renewable energy; Fossil fuel; Emerging technologies; Energy transition; Environmental economics; Offshore wind power; Carbon capture and storage (timeline); Leverage (statistics); Electricity generation; Upstream (networking); Natural gas; Dispatchable generation; Business; Scope (computer science); Environmental science; Wind power; Engineering; Computer science; Climate change; Telecommunications; Waste management; Distributed generation; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008117525,0.0000677615,0.00009332618,0.000125904,0.00003653926,0.000005887975,0.0001036058,0.00005006644,5.990464e-7],"category_scores_gemma":[0.00001148536,0.00005511173,0.00001521054,0.0007919923,0.000007037409,0.00003078463,0.000005805457,0.00006210589,8.495198e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003803567,"about_ca_system_score_gemma":0.00006536506,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5737644,"about_ca_topic_score_gemma":0.7978361,"domain_scores_codex":[0.9994538,0.00002130127,0.0001835755,0.00006474875,0.0001034135,0.000173167],"domain_scores_gemma":[0.9997934,0.00003470365,0.00002246244,0.0001154537,0.00002609958,0.000007949782],"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":[0.000001624428,6.760657e-7,0.0000427536,0.00001434148,0.00001037009,0.000003116476,0.000056036,0.9737045,0.004014099,0.01126018,0.0001327391,0.01075952],"study_design_scores_gemma":[0.00004517406,0.00000343312,0.00005738293,0.00003812557,0.000001850158,0.000001754314,0.003639689,0.893963,0.09925728,0.00008685177,0.00284459,0.00006088159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9129331,0.006393014,0.0319628,0.000433913,0.001897162,0.0002751246,0.0000278676,0.005532511,0.04054449],"genre_scores_gemma":[0.999731,0.0001491473,0.00002224638,0.000001165708,0.00001123805,0.00003053667,0.00000963406,0.00001522778,0.00002977351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2240716,"threshold_uncertainty_score":0.4290739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001895724675057051,"score_gpt":0.1455263783484142,"score_spread":0.1436306536733572,"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."}}