{"id":"W4205974867","doi":"10.1016/j.est.2022.103962","title":"Effective microwave-hydrothermal reduction of graphene oxide for efficient energy storage","year":2022,"lang":"en","type":"article","venue":"Journal of Energy Storage","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Graphene; Supercapacitor; Oxide; Materials science; Pseudocapacitance; Capacitance; Chemical engineering; Hydrothermal circulation; Energy storage; Nanotechnology; Electrode; Specific energy; Chemistry; Metallurgy","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":[0.00007742595,0.000207459,0.0001558156,0.0001757912,0.0001584018,0.0002315045,0.0003074343,0.0002209815,0.001240892],"category_scores_gemma":[0.000109897,0.0001259401,0.0001661452,0.0001277237,0.0001578192,0.000297693,0.0002301174,0.0003511447,0.0002261228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002337241,"about_ca_system_score_gemma":0.0001433185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005589701,"about_ca_topic_score_gemma":0.002661265,"domain_scores_codex":[0.9999458,0.000004735611,0.000003480324,0.0000092853,0.00002230627,0.00001447604],"domain_scores_gemma":[0.9999783,0.000005684707,0.000003969667,0.000003768767,0.00000430658,0.000004052083],"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":[0.00005831875,0.00003407371,0.00008772114,0.0001431677,0.00001229631,0.00005307704,0.00003596332,0.000318444,0.992291,0.0007641513,0.0004222391,0.005779531],"study_design_scores_gemma":[0.00001494369,0.00009593051,0.0007849388,0.0000059728,0.00001270707,0.00005433981,0.00002433397,0.0038167,0.9916806,0.0001335314,0.003367319,0.000008752671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856538,0.002276905,0.004949758,0.0002487755,0.0001328167,0.00002421819,0.0001652193,0.0001199101,0.006428667],"genre_scores_gemma":[0.9961786,0.0004285859,0.00145103,0.00002425411,0.00001656173,0.000008256054,0.00005959309,0.0000129999,0.00182011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001240892,"threshold_uncertainty_score":0.004151165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00886158384486756,"score_gpt":0.2203421011319332,"score_spread":0.2114805172870657,"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."}}