{"id":"W3133216924","doi":"","title":"An advanced ageing methodology for robustness assessment of normally-off AlGaN/GaN HEMT","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"High-electron-mobility transistor; Materials science; Optoelectronics; Robustness (evolution); Reliability (semiconductor); Wide-bandgap semiconductor; Stress (linguistics); Transistor; Gallium nitride; Threshold voltage; Voltage; Electronic engineering; Electrical engineering; Nanotechnology; Engineering; Chemistry; Layer (electronics); Power (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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004871052,0.0003263079,0.0006526798,0.0001441645,0.0001178074,0.0002381896,0.0008903296,0.000309921,0.0001336223],"category_scores_gemma":[0.0005742967,0.0003674147,0.0001908231,0.0001725962,0.00008593704,0.000209044,0.0003713895,0.0003360962,6.415993e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009050497,"about_ca_system_score_gemma":0.0001752362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670052,"about_ca_topic_score_gemma":0.0008906443,"domain_scores_codex":[0.9951954,0.003046806,0.0006501326,0.0005569921,0.0002234528,0.0003272406],"domain_scores_gemma":[0.9949668,0.001540375,0.000361169,0.001602211,0.001405086,0.0001243342],"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":[0.00001488348,0.0002672767,0.0003364331,0.001627037,0.0002032882,0.000006104156,0.00483427,0.08807057,0.8720857,0.004387986,0.00005878041,0.02810769],"study_design_scores_gemma":[0.0005548267,8.367724e-7,0.003393891,0.001289401,0.00008591573,0.000006972396,0.0005658133,0.2672356,0.7248803,0.000339314,0.001122844,0.0005242149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6253092,0.001223203,0.3699642,0.0001686375,0.0006101081,0.0003212321,0.00006387284,0.0002008745,0.002138703],"genre_scores_gemma":[0.6642003,0.0004793267,0.3343471,0.00001797958,0.0000274759,0.00007404144,0.0006933949,0.0000576231,0.0001027888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1791651,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03172947183927324,"score_gpt":0.2911733752834393,"score_spread":0.2594439034441661,"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."}}