{"id":"W2074424751","doi":"10.1063/1.2349314","title":"Electron mobility in dilute GaAs bismide and nitride alloys measured by time-resolved terahertz spectroscopy","year":2006,"lang":"en","type":"article","venue":"Applied Physics Letters","topic":"Terahertz technology and applications","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta","funders":"","keywords":"Electron mobility; Terahertz radiation; Conductivity; Materials science; Drude model; Terahertz spectroscopy and technology; Spectroscopy; Electron; Electron density; Nitride; Condensed matter physics; Analytical Chemistry (journal); Wide-bandgap semiconductor; Electrical resistivity and conductivity; Charge-carrier density; Optoelectronics; Chemistry; Nanotechnology; Physics; Doping; Physical chemistry","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":[0.0001281477,0.0002330947,0.0001944822,0.0002470693,0.0001823666,0.0003044394,0.0002287002,0.0002057854,0.0004141795],"category_scores_gemma":[0.000323303,0.0001441719,0.00008894257,0.0001513109,0.0002106662,0.0002364537,0.0002297762,0.0002439724,0.0001167862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000302253,"about_ca_system_score_gemma":0.0000891586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001349584,"about_ca_topic_score_gemma":0.001398599,"domain_scores_codex":[0.9999166,0.00001107319,0.00000378935,0.00001762987,0.00003518563,0.00001581678],"domain_scores_gemma":[0.999913,0.00003341599,0.00001804856,0.000006158248,0.00002039136,0.000009085657],"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":[0.00003993228,0.00000659152,0.000345394,0.0000128498,0.00000386649,0.00002547329,0.00004899297,0.0001763971,0.9986506,0.0001099972,0.00000835789,0.0005716456],"study_design_scores_gemma":[0.00001404021,0.0001856431,0.003605928,0.000008090375,0.00001760238,0.000111795,0.0001396164,0.005745211,0.989369,0.0001578936,0.0006348999,0.00001027327],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978811,0.0004202963,0.001089708,0.00002698736,0.000004078463,0.000004248736,0.00003407198,0.00001121034,0.000528346],"genre_scores_gemma":[0.9970478,0.0003764303,0.001421821,0.00001568559,0.000003005825,0.00001092664,0.00007284122,0.000004567096,0.001046998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001349584,"threshold_uncertainty_score":0.002683401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003327719835175964,"score_gpt":0.1813390732440679,"score_spread":0.1780113534088919,"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."}}