{"id":"W2884035048","doi":"10.1002/adma.201707424","title":"Strong Graphene 3D Assemblies with High Elastic Recovery and Hardness","year":2018,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Graphene research and applications","field":"Materials Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Science Foundation of Zhejiang Province; Argonne National Laboratory; Vehicle Technologies Office; Chinese Academy of Sciences; Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences; U.S. Department of Energy; Office of Energy Efficiency and Renewable Energy; National Natural Science Foundation of China","keywords":"Graphene; Materials science; Nanopore; Nanotechnology; Oxide; Composite material; Elastic modulus; Thermal stability; Chemical engineering","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":[0.00008406239,0.0004285208,0.0001480467,0.0003315115,0.0001749866,0.0002248559,0.0001620112,0.0003541967,0.000963753],"category_scores_gemma":[0.0001328262,0.0002358714,0.0003025528,0.000169748,0.0001727385,0.0002682781,0.0003565049,0.0003952179,0.0005064462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001326657,"about_ca_system_score_gemma":0.00006641228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001423991,"about_ca_topic_score_gemma":0.0006886369,"domain_scores_codex":[0.9999095,0.000009205752,0.000006374637,0.00001831765,0.00003457137,0.00002206004],"domain_scores_gemma":[0.9999171,0.00001251001,0.00002563465,0.00001257734,0.00001367112,0.00001844408],"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":[0.00001016676,0.000005833592,0.00008459241,0.00003320859,0.000006386736,0.00005743345,0.00001616422,0.0002338466,0.9971588,0.0001468318,0.00006669536,0.002179938],"study_design_scores_gemma":[0.000004522121,0.00009343804,0.001896112,0.000003193145,0.0000136433,0.0001299832,0.00001839974,0.001479294,0.9931786,0.00008721877,0.003084413,0.00001125032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9669901,0.001466677,0.02408086,0.000141927,0.00008977546,0.00004016363,0.000349015,0.0007122201,0.006129393],"genre_scores_gemma":[0.990858,0.0002915653,0.007109963,0.00004691219,0.000009798011,0.00002116223,0.0001654669,0.00003502076,0.001462076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000963753,"threshold_uncertainty_score":0.003224075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01295655737127157,"score_gpt":0.2701009756078309,"score_spread":0.2571444182365594,"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."}}