{"id":"W2996818948","doi":"10.1002/smll.201906540","title":"2D Antimony–Arsenic Alloys","year":2019,"lang":"en","type":"article","venue":"Small","topic":"2D Materials and Applications","field":"Materials Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McGill University; Polytechnique Montréal","funders":"PRIMA Québec; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Antimony; Arsenic; Raman spectroscopy; X-ray photoelectron spectroscopy; Materials science; Alloy; Arsenide; Graphene; Arsine; Heterojunction; Molecular beam epitaxy; Semiconductor; Epitaxy; Chemical engineering; Nanotechnology; Metallurgy; Chemistry; Gallium arsenide; Optoelectronics; Catalysis","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001530225,0.00007703905,0.0001128243,0.00001816929,0.00004606215,0.00006658433,0.0002106473,0.00004087184,0.003797486],"category_scores_gemma":[0.000007271491,0.00006581209,0.00003236128,0.00005467248,0.00002513809,0.00005976074,0.00007020436,0.00003036547,0.01392382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001040673,"about_ca_system_score_gemma":0.00002322928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006181195,"about_ca_topic_score_gemma":0.00001451369,"domain_scores_codex":[0.9993563,0.0000192111,0.0001334959,0.0002141504,0.00008068276,0.0001961473],"domain_scores_gemma":[0.9995288,0.00001940127,0.000047331,0.0003327223,0.00002469053,0.00004704351],"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":[0.000003803292,0.00002118634,0.0003876652,0.00001068235,0.000001250478,7.70078e-7,0.00003422173,0.0000106988,0.99204,0.006368773,0.000923876,0.00019701],"study_design_scores_gemma":[0.0003123748,0.00004765111,0.006890025,0.0000162158,0.00001031953,0.000007084745,0.00004160378,0.00007125367,0.8720334,0.001961638,0.1183855,0.0002229581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848087,0.00002968279,0.000115991,0.0002905324,0.0004940953,0.0001822931,0.00001731729,0.0001085535,0.01395285],"genre_scores_gemma":[0.9935321,0.000009828837,0.002635331,0.0002545768,0.000109138,0.00001999187,0.000007226193,0.00001318792,0.003418582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1200067,"threshold_uncertainty_score":0.9971132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706625599520753,"score_gpt":0.2342634858031839,"score_spread":0.2171972298079764,"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."}}