{"id":"W4210880463","doi":"10.1109/iaecst54258.2021.9695865","title":"Flow battery: An energy storage alternative for hydropower station","year":2021,"lang":"en","type":"article","venue":"2021 3rd International Academic Exchange Conference on Science and Technology Innovation (IAECST)","topic":"Advanced battery technologies research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Dalhousie University","funders":"","keywords":"Flow battery; Energy storage; Renewable energy; Vanadium; Battery (electricity); Process engineering; Pumped-storage hydroelectricity; Environmental science; Energy flow; Computer data storage; Computer science; Waste management; Engineering; Electrical engineering; Energy (signal processing); Power (physics); Materials science; Distributed generation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005867794,0.0002991805,0.0002621373,0.0006402032,0.0003256621,0.0004697758,0.0006266189,0.0004740059,0.01235387],"category_scores_gemma":[0.00007561852,0.0001107526,0.0002652867,0.0005310397,0.0001385364,0.001300526,0.0003725032,0.0002872575,0.003188098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000193835,"about_ca_system_score_gemma":0.0002220047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004330606,"about_ca_topic_score_gemma":0.0007054509,"domain_scores_codex":[0.9999342,0.000004307071,0.000003550385,0.00001355413,0.0000335378,0.00001081691],"domain_scores_gemma":[0.9999756,0.000002007153,0.000002690513,0.000002539909,0.00001216442,0.000005035118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009729338,0.0003885468,0.001823886,0.002327719,0.00008696473,0.001493772,0.0001131414,0.004018357,0.3921271,0.01510462,0.03534228,0.5462008],"study_design_scores_gemma":[0.0002901591,0.001791895,0.005560336,0.0002917591,0.0001789162,0.003596158,0.0002534535,0.03177645,0.3312179,0.01321516,0.6116917,0.0001360837],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5736632,0.04209631,0.1379952,0.005069342,0.00467459,0.000602187,0.007550254,0.007771727,0.2205772],"genre_scores_gemma":[0.8818723,0.01022532,0.01319208,0.0006312516,0.000417753,0.000118784,0.002284632,0.0001375549,0.09112029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01235387,"threshold_uncertainty_score":0.04132777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05103451219450508,"score_gpt":0.3432801501111393,"score_spread":0.2922456379166343,"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."}}