{"id":"W2995145484","doi":"10.1073/pnas.1821686116","title":"Renewable electricity storage using electrolysis","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":245,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research; U.S. Department of Energy","keywords":"Electrolysis; Renewable energy; Electrolysis of water; Energy storage; Chemical energy; Process engineering; Electricity; Power to gas; Polymer electrolyte membrane electrolysis; Environmental science; High-temperature electrolysis; Waste management; Chemistry; Electrolyte; Engineering; Electrode; Electrical engineering; Power (physics); Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001494132,0.0002872115,0.0004557397,0.0004037064,0.0002987085,0.001198274,0.0005323237,0.0006056888,0.004102145],"category_scores_gemma":[0.0002624897,0.0001769122,0.0002306021,0.0006414265,0.0003102953,0.001828966,0.0007074454,0.0005508478,0.001588937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003512075,"about_ca_system_score_gemma":0.0002386006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004460081,"about_ca_topic_score_gemma":0.0007584625,"domain_scores_codex":[0.999821,0.00001531387,0.00001361776,0.00004226194,0.00008850507,0.00001930567],"domain_scores_gemma":[0.9999332,0.0000163137,0.000008170214,0.00001312125,0.00002299199,0.000006027671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001864091,0.0001260915,0.0007630537,0.001863267,0.00008638648,0.0007478041,0.0001380211,0.005907595,0.7104733,0.03693829,0.01017004,0.2325997],"study_design_scores_gemma":[0.00005129561,0.000292857,0.001189381,0.0001789947,0.00006801264,0.0009354812,0.0001425668,0.02271304,0.7616671,0.01050319,0.2021912,0.00006699684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3990514,0.1302727,0.2371379,0.004328449,0.003670399,0.0002632595,0.00155154,0.004159208,0.2195651],"genre_scores_gemma":[0.9188067,0.02982887,0.01850168,0.0002878938,0.0002196058,0.00004462175,0.0004470933,0.00009246741,0.0317711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004102145,"threshold_uncertainty_score":0.01372302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02795420704674899,"score_gpt":0.28898351385107,"score_spread":0.261029306804321,"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."}}