{"id":"W2740710104","doi":"10.1039/c7tc02487h","title":"A sustainable approach to large area transfer of graphene and recycling of the copper substrate","year":2017,"lang":"en","type":"article","venue":"Journal of Materials Chemistry C","topic":"Graphene research and applications","field":"Materials Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Division of Civil, Mechanical and Manufacturing Innovation; Natural Sciences and Engineering Research Council of Canada; National Aeronautics and Space Administration","keywords":"Materials science; Graphene; Copper; Substrate (aquarium); Delamination (geology); Electrolyte; Electrochemistry; Chemical engineering; Nanotechnology; Metallurgy; Electrode; Chemistry","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":[0.0002912279,0.0006392596,0.0002980201,0.0006135154,0.0005009152,0.000784851,0.0009153722,0.001165137,0.001153381],"category_scores_gemma":[0.0003587306,0.0003426134,0.0003326985,0.0004384801,0.000513219,0.0009621576,0.000687284,0.001211175,0.000611116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000655766,"about_ca_system_score_gemma":0.0006614131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004546313,"about_ca_topic_score_gemma":0.001112544,"domain_scores_codex":[0.9996749,0.00003508532,0.00001809624,0.00006004352,0.0001611662,0.0000506826],"domain_scores_gemma":[0.9998579,0.00002192599,0.00002336633,0.00003413957,0.00003314233,0.00002957065],"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":[0.00003344058,0.00005656323,0.0001278912,0.0001729102,0.00001479296,0.0002260875,0.00004100552,0.0007515837,0.9762986,0.007191047,0.000832328,0.01425389],"study_design_scores_gemma":[0.000008516388,0.0001399213,0.0002004046,0.00001024347,0.000009573552,0.0003430987,0.00002228885,0.003729603,0.9835646,0.001248786,0.01070389,0.00001902955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7359151,0.01826486,0.2108404,0.003477115,0.0009724328,0.000316871,0.0007626492,0.002103501,0.0273471],"genre_scores_gemma":[0.9206949,0.004884647,0.0646912,0.0002744428,0.00006467199,0.0001187463,0.0003542309,0.00007779023,0.008839412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001165137,"threshold_uncertainty_score":0.004757941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284192987737165,"score_gpt":0.2717733038490481,"score_spread":0.2489313739716765,"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."}}