{"id":"W2796256597","doi":"10.1109/ted.2018.2817509","title":"An Improved Nonlocal History-Dependent Model for Gain and Noise in Avalanche Photodiodes Based on Energy Balance Equation","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Electron Devices","topic":"Semiconductor Quantum Structures and Devices","field":"Physics and Astronomy","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Avalanche photodiode; APDS; Impact ionization; Noise (video); Physics; Ionization; Computational physics; Optoelectronics; Classification of discontinuities; Diode; Computer science; Optics; Mathematics; Quantum mechanics; Detector; Mathematical analysis; Ion; Artificial intelligence","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":[0.0005837799,0.0008472044,0.0009429224,0.0006346935,0.0004257456,0.001032503,0.002604102,0.001601355,0.003007181],"category_scores_gemma":[0.001078908,0.0005504563,0.001299866,0.0005452566,0.0006634187,0.002498738,0.0007861988,0.001090925,0.0006376423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001528971,"about_ca_system_score_gemma":0.0007489599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004450162,"about_ca_topic_score_gemma":0.003253178,"domain_scores_codex":[0.9996769,0.0000495867,0.00001811081,0.00008452384,0.0001318268,0.00003900807],"domain_scores_gemma":[0.9996555,0.0001314218,0.00004592977,0.00003511423,0.0001114302,0.00002063352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005180731,0.00005273871,0.0008069038,0.00009757807,0.00005518921,0.0003012242,0.0001468839,0.930312,0.01917044,0.0398381,0.0006253456,0.00854187],"study_design_scores_gemma":[0.000003365303,0.000008473646,0.00009233709,0.000002474715,0.000005631224,0.00001876065,0.0000037341,0.9967545,0.0004912198,0.002331928,0.0002816516,0.000005898608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03222289,0.0005383478,0.9583896,0.0002261516,0.00006977347,0.00009165656,0.0002051823,0.0002585204,0.007997784],"genre_scores_gemma":[0.8835579,0.001273468,0.065955,0.0003474929,0.0001134677,0.0005792869,0.0003903998,0.0002760635,0.04750712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004450162,"threshold_uncertainty_score":0.01109344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01800464393588902,"score_gpt":0.2577559262846619,"score_spread":0.2397512823487729,"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."}}