{"id":"W4387037376","doi":"10.1016/j.carbon.2023.118472","title":"Boron carbon nitride nanosheets via induction plasma: Insights on synthesis, characterization, and control of band gap","year":2023,"lang":"en","type":"article","venue":"Carbon","topic":"Graphene research and applications","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Department of Chemical Engineering, Monash University; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Band gap; Raman spectroscopy; Nanosheet; Analytical Chemistry (journal); Spectroscopy; Scanning electron microscope; Ammonia borane; Boron nitride; Carbon fibers; Carbon nitride; Fourier transform infrared spectroscopy; Boron; Chemical engineering; Nanotechnology; Chemistry; Composite material; Optoelectronics; Hydrogen storage; Optics; Composite number; Photocatalysis","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":[0.0002046053,0.0001088648,0.0001825087,0.0001886205,0.00008278382,0.00002837657,0.0001029976,0.00007687317,0.00001154723],"category_scores_gemma":[0.0001263418,0.00009574649,0.00002453856,0.0003576003,0.00009680158,0.0000637612,0.0000214321,0.00007166032,0.000012738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002503748,"about_ca_system_score_gemma":0.00003998974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001257581,"about_ca_topic_score_gemma":0.00001423944,"domain_scores_codex":[0.9989854,0.00008937384,0.0002002476,0.0002622629,0.0002490912,0.0002136283],"domain_scores_gemma":[0.9993553,0.0001427136,0.00009680955,0.0002256291,0.00008542655,0.00009413825],"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":[0.00004891989,0.00002879603,0.0007796336,0.0000278628,0.000006700672,0.000001805584,0.00009680919,0.000009084239,0.9978471,0.00023545,0.0000148723,0.0009029484],"study_design_scores_gemma":[0.0003149811,0.00006990569,0.02614982,0.00003981469,0.0000156839,0.000001956607,0.0000275415,0.001381735,0.9712297,0.0004200118,0.0002510471,0.00009778324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984436,0.00005516146,0.00004850878,0.000304935,0.0001349108,0.0002966113,0.00002875947,0.0000787154,0.000608801],"genre_scores_gemma":[0.9995485,0.0001302117,0.000006854315,0.0000164538,0.00008383488,0.0001255259,0.00002323968,0.00001466175,0.00005069458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0266174,"threshold_uncertainty_score":0.3904428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702544675294438,"score_gpt":0.2402114245937418,"score_spread":0.2231859778407974,"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."}}