{"id":"W2228804616","doi":"10.1038/srep23233","title":"Superhigh moduli and tension-induced phase transition of monolayer gamma-boron at finite temperatures","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"MXene and MAX Phase Materials","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Jiangsu Province; Fundamental Research Funds for the Central Universities; Nanjing University of Aeronautics and Astronautics; Institute of Nutrition, Metabolism and Diabetes; State Key Laboratory of Mechanics and Control of Mechanical Structures; National Natural Science Foundation of China","keywords":"Monolayer; Zigzag; Boron; Phase transition; Tension (geology); Materials science; Molecular dynamics; Phase (matter); Moduli; Chemical physics; Thermodynamics; Chemistry; Nanotechnology; Composite material; Computational chemistry; Physics; Organic chemistry; Ultimate tensile strength; Geometry","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":[0.00005522466,0.0002623354,0.0001077664,0.000134087,0.0001809161,0.0001979917,0.0002327516,0.0002395249,0.001043135],"category_scores_gemma":[0.0001483505,0.0002125983,0.0001463826,0.00008045942,0.0003126748,0.000435747,0.0001928375,0.0002816614,0.00008697855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001909651,"about_ca_system_score_gemma":0.0001692223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007084737,"about_ca_topic_score_gemma":0.001046371,"domain_scores_codex":[0.9999754,0.000002601549,0.000001358626,0.000005444063,0.000008850671,0.000006370663],"domain_scores_gemma":[0.9999686,0.00001200953,0.000008953266,0.000003335117,0.00000350629,0.000003600101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001761727,0.0000625492,0.003461795,0.0002780406,0.00002464726,0.000310177,0.0001406995,0.04260888,0.9422312,0.007674437,0.0003115719,0.002719922],"study_design_scores_gemma":[0.00009338152,0.0002624262,0.01147253,0.00002726186,0.00002113926,0.0001639982,0.0001299998,0.4094971,0.5707809,0.006173037,0.001328392,0.00004981455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971438,0.0001345975,0.001526705,0.00006915989,0.000007296034,0.000004989794,0.00006765322,0.00003301078,0.001012764],"genre_scores_gemma":[0.9990065,0.0001101111,0.0006222177,0.000008980499,0.000001571956,0.000009358889,0.00006996411,0.000007550822,0.0001638918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001043135,"threshold_uncertainty_score":0.003489673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975216944799027,"score_gpt":0.2631933518437374,"score_spread":0.2434411823957472,"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."}}