{"id":"W4386855340","doi":"10.1149/ma2023-0181091mtgabs","title":"Optimized Graphene Hydrogels for Electrochemical Applications from High-Concentration GO/Gnp Dispersions","year":2023,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Self-healing hydrogels; Graphene; Supercapacitor; Materials science; Specific surface area; Nanotechnology; Energy storage; Chemical engineering; Oxide; Conductivity; Adsorption; Electrode; Electrochemistry; Chemistry; Power (physics); Polymer chemistry","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":[0.00014631,0.0005533434,0.0001810849,0.0003099361,0.0001067123,0.0001840869,0.0002523522,0.0003119207,0.0005918462],"category_scores_gemma":[0.0001833505,0.0001518451,0.0002351116,0.0002642285,0.0001507859,0.0002259429,0.0001446686,0.0003478447,0.0001387298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377939,"about_ca_system_score_gemma":0.0001280846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003719619,"about_ca_topic_score_gemma":0.001530163,"domain_scores_codex":[0.9998732,0.00001357946,0.0000134583,0.00002707744,0.00005070092,0.0000219984],"domain_scores_gemma":[0.9999137,0.00002097424,0.00002853514,0.00000617909,0.00001699918,0.0000135761],"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":[0.00001817733,0.00001010825,0.00001622197,0.00002682078,0.000002215065,0.00001457277,0.000004677916,0.0001654417,0.9991787,0.00001618043,0.0000100257,0.0005367122],"study_design_scores_gemma":[0.000004684798,0.00006501069,0.0002559331,0.000002583232,0.000004371479,0.00001590038,0.000003467321,0.0006385791,0.9986992,0.000009441627,0.0002976175,0.000003220868],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868233,0.001191047,0.009770872,0.00007615577,0.00003721077,0.000107309,0.000500554,0.0001189385,0.00137476],"genre_scores_gemma":[0.9773563,0.00106872,0.01968937,0.00004600766,0.000007920749,0.0001314004,0.0003955019,0.00004240761,0.001262413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005918462,"threshold_uncertainty_score":0.002450883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01562529712417245,"score_gpt":0.2463944018472054,"score_spread":0.230769104723033,"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."}}