{"id":"W4416410856","doi":"10.1016/j.cartre.2025.100592","title":"Evidence of plasma-driven nonequilibrium chemistry in graphene formation from gas-phase kinetic modeling","year":2025,"lang":"en","type":"article","venue":"Carbon Trends","topic":"Graphene research and applications","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Graphene; Non-equilibrium thermodynamics; Thermodynamic equilibrium; Chemical equilibrium; Yield (engineering); Kinetics; Plasma; Kinetic energy; Molecular dynamics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001486897,0.0001003672,0.0001771307,0.0001906632,0.00002803092,0.00002778111,0.0002776082,0.00005291053,0.00008103326],"category_scores_gemma":[0.00006508968,0.0001000957,0.00005505415,0.0007238498,0.00006475318,0.0001799234,0.00007473085,0.00009288268,0.000003204068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000402595,"about_ca_system_score_gemma":0.00005848303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004378718,"about_ca_topic_score_gemma":0.00006331416,"domain_scores_codex":[0.9989608,0.00003593137,0.0003297763,0.0002416702,0.0002040275,0.000227775],"domain_scores_gemma":[0.9993738,0.00008239085,0.00007076064,0.0003416474,0.00006640566,0.00006498349],"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":[0.00005739031,0.00006968301,0.0001906156,0.00006168491,0.000003377184,0.000001299699,0.00009374167,0.004388697,0.9925811,0.0001062785,0.00002297728,0.002423181],"study_design_scores_gemma":[0.0005242384,0.00002059611,0.0002344143,0.0002327492,0.0000110267,3.874193e-7,0.00004785752,0.443325,0.5548558,0.0006705586,0.000009142349,0.00006816193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957976,0.0005067733,0.001125679,0.000232609,0.00003927968,0.00007001428,0.00003017527,0.00003440208,0.002163404],"genre_scores_gemma":[0.999204,0.0001121503,0.0004965799,0.000006771992,0.00001999753,0.00006708896,0.00003003868,0.00000581782,0.00005755335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4389363,"threshold_uncertainty_score":0.4081783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03598506149025617,"score_gpt":0.3161645148614052,"score_spread":0.2801794533711491,"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."}}