{"id":"W3045366189","doi":"10.1016/j.sse.2020.107869","title":"New accurate approximation of the Einstein Relation for heavily-doped semiconductor devices","year":2020,"lang":"en","type":"article","venue":"Solid-State Electronics","topic":"Advanced Materials and Semiconductor Technologies","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Einstein relation; Einstein; Degeneracy (biology); Doping; Relation (database); Semiconductor; Scaling; Physics; Quality (philosophy); Fermi Gamma-ray Space Telescope; Constant (computer programming); Condensed matter physics; Theoretical physics; Statistical physics; Quantum mechanics; Mathematics; Computer science; Geometry; Data mining; Bioinformatics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000199723,0.0001968324,0.0003070612,0.00003057495,0.0001434188,0.00006093986,0.0004781964,0.0001077932,0.0000685267],"category_scores_gemma":[0.000271231,0.0001440762,0.00008666493,0.0002420179,0.00007063444,0.0004421602,0.0001107355,0.0001415552,0.0000153546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008650521,"about_ca_system_score_gemma":0.0002533669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001397241,"about_ca_topic_score_gemma":0.00003477961,"domain_scores_codex":[0.9985151,0.00005598618,0.0004792577,0.0003438961,0.0001922197,0.0004135837],"domain_scores_gemma":[0.9989982,0.00007082713,0.0004463399,0.0003102044,0.0001129617,0.0000614563],"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":[0.00008519398,0.00000973032,0.00001983607,0.00008596898,0.000009003023,1.562776e-7,0.0004373124,0.001168657,0.9924342,0.004491412,0.0004492309,0.0008093126],"study_design_scores_gemma":[0.0004596077,0.0001699193,0.00003236413,0.00002652631,0.00002330608,0.000001746072,0.0001376106,0.001461915,0.9759322,0.01529306,0.006289741,0.0001720445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981836,0.0006523925,0.0144798,0.001568601,0.0003437897,0.0007555136,0.00008881805,0.0002214004,0.00005366535],"genre_scores_gemma":[0.9929487,0.0001272686,0.006334228,0.0002609726,0.00009392788,0.0000351262,0.00002769794,0.0000331381,0.0001389873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01650202,"threshold_uncertainty_score":0.5875257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02900415011866639,"score_gpt":0.2793643605244826,"score_spread":0.2503602104058162,"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."}}