{"id":"W2803468448","doi":"10.1039/c8nr02451k","title":"Atomic-scale etching of hexagonal boron nitride for device integration based on two-dimensional materials","year":2018,"lang":"en","type":"article","venue":"Nanoscale","topic":"Graphene research and applications","field":"Materials Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Ministry of Science, ICT and Future Planning","keywords":"Etching (microfabrication); Materials science; Hexagonal boron nitride; Atomic units; Boron nitride; Hexagonal crystal system; Dry etching; Nanotechnology; Scale (ratio); Nitride; Boron; Optoelectronics; Crystallography; Chemistry; Physics","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":[0.0000936194,0.0002673961,0.0001812068,0.0001673194,0.0001624202,0.0001683528,0.0003256283,0.0002482336,0.0003238787],"category_scores_gemma":[0.0001089654,0.0001709248,0.0001552079,0.00009974201,0.0001249059,0.0002269505,0.000266312,0.0001853975,0.0001350746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648528,"about_ca_system_score_gemma":0.000120795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003917366,"about_ca_topic_score_gemma":0.001113334,"domain_scores_codex":[0.999921,0.000007837252,0.000004499851,0.00001881998,0.00003397112,0.0000138555],"domain_scores_gemma":[0.9999603,0.000009852644,0.00001112584,0.000008254062,0.000005751794,0.000004779914],"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":[0.000009524785,0.000008324987,0.0001043702,0.00002789741,0.000002599133,0.00002710147,0.000007941985,0.0001447846,0.9980164,0.0001338883,0.00001730642,0.001499891],"study_design_scores_gemma":[0.000004671243,0.00007961006,0.0009470712,0.000002557951,0.000004582395,0.0001127107,0.000009108368,0.003387386,0.9942816,0.00005574797,0.001107938,0.000006954544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9678431,0.001471015,0.0270633,0.00006186974,0.00007675041,0.00006060743,0.0002175002,0.0001773148,0.003028624],"genre_scores_gemma":[0.9591709,0.000714907,0.03914991,0.00002928839,0.0000128673,0.00004129396,0.0001395279,0.00001507636,0.0007262209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003917366,"threshold_uncertainty_score":0.001196086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02350716892742942,"score_gpt":0.3163982795565671,"score_spread":0.2928911106291376,"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."}}