{"id":"W2166520016","doi":"10.1109/led.2014.2298457","title":"Optimized Pre-Treatment Process for MOS-GaN Devices Passivation","year":2014,"lang":"en","type":"article","venue":"IEEE Electron Device Letters","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Passivation; Materials science; High-electron-mobility transistor; Optoelectronics; Capacitance; Capacitor; Gallium nitride; Analytical Chemistry (journal); Transistor; Electronic engineering; Electrical engineering; Voltage; Nanotechnology; Chemistry; Electrode; Layer (electronics)","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":[0.0001178613,0.000499052,0.0003098507,0.0001744769,0.0001529812,0.0002904246,0.0003554122,0.0003053553,0.001190868],"category_scores_gemma":[0.0001435169,0.0001750983,0.000232114,0.0001784708,0.0001165092,0.0002150745,0.0001408362,0.000407929,0.0003788347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002177108,"about_ca_system_score_gemma":0.0002709531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005888689,"about_ca_topic_score_gemma":0.001549412,"domain_scores_codex":[0.999877,0.00001075735,0.00001010895,0.00003775175,0.00004223308,0.00002222373],"domain_scores_gemma":[0.9999357,0.00001150966,0.00001929691,0.00001093611,0.00001888142,0.000003658229],"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":[0.00001713116,0.00001225433,0.0001621838,0.00009218623,0.000009783966,0.00003002468,0.00001107712,0.0002445369,0.9965229,0.00008397935,0.00008146143,0.002732606],"study_design_scores_gemma":[0.000005670503,0.00008968464,0.001302313,0.000003773661,0.00001456054,0.00008130584,0.00001091333,0.001274255,0.9950436,0.0000289172,0.002138646,0.00000623496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9353664,0.004467444,0.05424847,0.0001874205,0.0002601202,0.0002616928,0.0006872681,0.0004915476,0.004029695],"genre_scores_gemma":[0.9476263,0.002273489,0.04682309,0.00008163596,0.00003862002,0.0001269714,0.0005245375,0.0001089004,0.002396427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001190868,"threshold_uncertainty_score":0.003983855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132556922726466,"score_gpt":0.2741700055751511,"score_spread":0.2609143133025045,"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."}}