{"id":"W4416537092","doi":"","title":"Probing Fermi Energy and Temperature-Dependent Shifts in Doped Homo-Epitaxial GaN Layers Using Micro-Raman Spectroscopy","year":2025,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Sherbrooke","funders":"","keywords":"Doping; Spectroscopy; Energy (signal processing); Fermi level; Fermi energy; Fermi Gamma-ray Space Telescope","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":[0.001029318,0.0002019374,0.0002568836,0.0001534729,0.0002387146,0.0003832598,0.0003118795,0.00007383344,0.00009449293],"category_scores_gemma":[0.00003244144,0.0002072253,0.00006355183,0.0002743721,0.00007925745,0.0001531218,0.0001601075,0.0001546826,0.000002553535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006399273,"about_ca_system_score_gemma":0.0001381615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004840772,"about_ca_topic_score_gemma":0.001663701,"domain_scores_codex":[0.9978601,0.0009718105,0.0003256197,0.000419365,0.0001201297,0.0003029838],"domain_scores_gemma":[0.9988437,0.0001807302,0.0001521522,0.0005125516,0.0002287223,0.00008215269],"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":[0.00001144457,0.000163226,0.00828903,0.00003154103,0.00003141342,0.000001668404,0.001501133,0.0000178023,0.9443591,0.04393552,0.00007150363,0.001586606],"study_design_scores_gemma":[0.0008025704,4.54206e-7,0.002621931,0.0005595666,0.00002499118,9.698226e-7,0.0003876834,0.0006581815,0.990856,0.002533941,0.001309646,0.0002440529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878922,0.0002548818,0.002426722,0.0008763396,0.0001639515,0.0002047686,0.00002704071,0.00004363004,0.008110495],"genre_scores_gemma":[0.995187,0.00002792942,0.003295932,0.00008405253,0.00002929717,0.00002087277,0.00008715234,0.0000207099,0.001246989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0464969,"threshold_uncertainty_score":0.8450403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008493895425264998,"score_gpt":0.229522023156109,"score_spread":0.221028127730844,"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."}}