{"id":"W2913032408","doi":"10.1063/1.5083168","title":"Uniqueness range optimization of photocarrier transport parameter measurements using combined quantitative heterodyne lock-in carrierography imaging and photocarrier radiometry","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Silicon and Solar Cell Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China-Yunnan Joint Fund; China Scholarship Council; Canada Research Chairs","keywords":"Radiometry; Heterodyne (poetry); Optics; Wafer; Range (aeronautics); Diffusion; Materials science; Masking (illustration); Computational physics; Physics; Optoelectronics; Acoustics","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":[0.000277127,0.0001987163,0.0004957963,0.0003194736,0.00002186225,0.0000179582,0.0001473245,0.0000885482,0.000009201745],"category_scores_gemma":[0.000005508249,0.0001934534,0.0001173568,0.0005821004,0.00009010992,0.0002011658,0.0000129661,0.0002684599,2.730887e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000610126,"about_ca_system_score_gemma":0.00002620522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008262257,"about_ca_topic_score_gemma":0.000001547433,"domain_scores_codex":[0.9988818,0.0000219922,0.0004882772,0.000136954,0.0002770399,0.0001939273],"domain_scores_gemma":[0.9994015,0.00005298447,0.0002193194,0.0001762181,0.00009340151,0.00005655417],"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":[0.0002162002,0.00004923546,0.09996095,0.0001607162,0.0001780605,0.00000525109,0.0007981298,0.7295655,0.1684088,0.00008754782,0.000002907972,0.0005666822],"study_design_scores_gemma":[0.004278326,0.0001657695,0.007462171,0.0002602146,0.0001543765,0.0000108061,0.002026371,0.5517486,0.4324202,0.0009562224,0.00002206374,0.0004948025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717609,0.000311713,0.02711356,0.000001689856,0.0001493609,0.0003748908,0.000006729451,0.00003358927,0.0002475221],"genre_scores_gemma":[0.9886672,0.00008000703,0.01117657,0.00001572683,0.00001240409,0.000006251712,0.000002887272,0.00003819549,6.818069e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2640114,"threshold_uncertainty_score":0.7888799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02082496817588557,"score_gpt":0.2381848758996241,"score_spread":0.2173599077237385,"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."}}