{"id":"W4413384133","doi":"10.1016/j.decarb.2025.100122","title":"Industrial scaling of molten carbonate electrolytic carbon capture and production of graphene allotropes","year":2025,"lang":"en","type":"article","venue":"DeCarbon","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"","keywords":"Carbonate; Graphene; Electrolyte; Scaling; Carbon fibers; Materials science; Chemical engineering; Environmental science; Metallurgy; Nanotechnology; Chemistry; Composite material; Electrode; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001508507,0.0001442131,0.0003001311,0.0001841663,0.00001311847,0.000007056178,0.0000890354,0.0001021024,0.000002526891],"category_scores_gemma":[0.00005331985,0.0001443071,0.00002234507,0.0002457576,0.00005600782,0.00005099645,0.00003465727,0.0001077528,8.224441e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003986471,"about_ca_system_score_gemma":0.00001629521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001007628,"about_ca_topic_score_gemma":0.000007721925,"domain_scores_codex":[0.9991397,0.00003137276,0.0003452138,0.0001781444,0.00013184,0.000173756],"domain_scores_gemma":[0.9996334,0.00002445944,0.00007328158,0.0002058065,0.00004207027,0.00002097146],"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":[0.0001094587,0.00002817486,0.004806336,0.0003168177,0.0001858685,0.000001891807,0.0002218566,0.02926314,0.9627516,0.0004754495,0.0000719468,0.0017675],"study_design_scores_gemma":[0.00108475,0.00007459155,0.003319796,0.0003607901,0.0001914814,0.000004164695,0.00007345036,0.008729513,0.9826552,0.002995566,0.0002146896,0.0002959929],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939342,0.0009683113,0.00003673663,0.00005047315,0.0009583334,0.0002330001,0.000004191802,0.00007123066,0.003743517],"genre_scores_gemma":[0.9995074,0.0001022907,0.0002078697,0.00001015556,0.00007779664,0.00001527209,0.000004667634,0.00002135593,0.00005319866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02053363,"threshold_uncertainty_score":0.5884672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008948628791450143,"score_gpt":0.2186223699829672,"score_spread":0.2096737411915171,"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."}}