{"id":"W4214637207","doi":"10.3390/electrochem3010010","title":"Graphene: Chemistry and Applications for Lithium-Ion Batteries","year":2022,"lang":"en","type":"article","venue":"Electrochem","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Graphene; Materials science; Nanotechnology; Anode; Cathode; Battery (electricity); Lithium (medication); Electrolyte; Engineering physics; Chemistry; Electrode; Physical chemistry; Physics","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":[0.0002650028,0.000738526,0.0004368938,0.001494449,0.0004403224,0.0007443505,0.0005318659,0.001158334,0.003069449],"category_scores_gemma":[0.0002285875,0.0002312642,0.0003902421,0.001418159,0.000444027,0.001252132,0.0008229688,0.00136476,0.001430063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005645509,"about_ca_system_score_gemma":0.0003502958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005529383,"about_ca_topic_score_gemma":0.001024785,"domain_scores_codex":[0.9998263,0.00002291913,0.00001266531,0.00002925601,0.00008487413,0.00002406019],"domain_scores_gemma":[0.9999413,0.00002040073,0.000008941451,0.000003427705,0.00001665367,0.000009203524],"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":[0.0001065191,0.0001412862,0.000428945,0.01930493,0.00006813446,0.001001084,0.0003275112,0.001990232,0.1152493,0.07799064,0.03467791,0.7487134],"study_design_scores_gemma":[0.000008627138,0.0001510697,0.000569278,0.001053803,0.00003748323,0.001277838,0.00009452157,0.0006418416,0.02548811,0.01481082,0.9558053,0.00006127265],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.003520666,0.9729392,0.003671373,0.001297146,0.0007768832,0.00002574781,0.0001088062,0.000067723,0.0175924],"genre_scores_gemma":[0.03393474,0.9554501,0.00346621,0.0006219933,0.0006669244,0.00004098982,0.0001253753,0.00001435011,0.005679276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003069449,"threshold_uncertainty_score":0.01026839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005732652200264453,"score_gpt":0.2178317769763105,"score_spread":0.2120991247760461,"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."}}