{"id":"W1797664886","doi":"10.1063/1.4930031","title":"Performance optimization of p-n homojunction nanowire-based piezoelectric nanogenerators through control of doping concentration","year":2015,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Homojunction; Nanowire; Materials science; Doping; Piezoelectricity; Nanogenerator; Optoelectronics; Nanotechnology; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001283601,0.0001006602,0.0002706197,0.00003271998,0.00002194331,0.000008647717,0.00006189646,0.00004686762,0.000002186065],"category_scores_gemma":[0.00001323754,0.00009395977,0.00004511576,0.0002225869,0.00002560106,0.0002117719,0.000002650329,0.00006668922,4.299313e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006162612,"about_ca_system_score_gemma":0.00006305167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001306861,"about_ca_topic_score_gemma":8.89471e-8,"domain_scores_codex":[0.9991972,0.0000142876,0.000432297,0.00005293726,0.0001975274,0.0001057568],"domain_scores_gemma":[0.9992401,0.0000273407,0.0003870286,0.00007833898,0.0002314776,0.00003570641],"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":[0.00009231485,0.00001961774,0.00006684932,0.00005484014,0.00002422786,2.125369e-7,0.00009556548,0.7868518,0.2111745,0.0002264942,0.00002073348,0.001372884],"study_design_scores_gemma":[0.000840016,0.00008008257,0.00001788712,0.00003772658,0.00002948385,0.000001308407,0.00001332736,0.5016995,0.4970655,0.0001195544,0.00003428744,0.00006136832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5349686,0.00005552136,0.4639495,0.00000168722,0.0002909992,0.00005137576,0.000002382699,0.00001634175,0.000663514],"genre_scores_gemma":[0.9902856,0.00005502892,0.009388577,0.00001270864,0.0002294547,0.00000199794,0.000006194614,0.00001900614,0.000001422086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.455317,"threshold_uncertainty_score":0.3831568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438604311592262,"score_gpt":0.2048773614905348,"score_spread":0.1904913183746122,"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."}}