{"id":"W2290897030","doi":"10.1007/s10765-016-2054-0","title":"Quantitative Carrier Density Wave Imaging in Silicon Solar Cells Using Photocarrier Radiometry and Lock-in Carrierography","year":2016,"lang":"en","type":"article","venue":"International Journal of Thermophysics","topic":"Silicon and Solar Cell Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Recruitment Program of Global Experts; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Heterodyne (poetry); Solar cell; Radiometry; Materials science; Optics; Optoelectronics; Silicon; Direct-conversion receiver; Heterodyne detection; Carrier lifetime; Physics; Homodyne detection; Laser","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":[0.0002064204,0.0001459023,0.0002296499,0.0005788191,0.00001630741,0.00003930839,0.0002197877,0.00006588356,0.00000984259],"category_scores_gemma":[0.00004757051,0.0001159524,0.0001002435,0.0002308099,0.0001102258,0.0003230929,0.0000485386,0.0002267326,0.000001004316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001849934,"about_ca_system_score_gemma":0.00002639825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003880026,"about_ca_topic_score_gemma":0.00001634246,"domain_scores_codex":[0.999088,0.00003733903,0.000337451,0.0001182985,0.0002432787,0.0001756334],"domain_scores_gemma":[0.9994981,0.0001170368,0.0001153172,0.0001045958,0.000114509,0.00005040616],"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":[0.00007032056,0.00002737994,0.05660646,0.000008785463,0.0001166585,0.000246189,0.0007354929,0.0009975024,0.9126403,0.0002086954,0.00001608204,0.02832615],"study_design_scores_gemma":[0.0023531,0.00008692844,0.03754709,0.0004648286,0.00003268257,0.0001648855,0.001725077,0.03932177,0.9109721,0.006639189,0.0002209323,0.0004714537],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952778,0.0005524074,0.003308685,0.00005746067,0.000596585,0.000067553,0.0000141166,0.00002567731,0.00009969077],"genre_scores_gemma":[0.9987516,0.000329554,0.0007978865,0.00003158284,0.00006225546,0.00000120174,3.288769e-7,0.00002243016,0.000003199275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03832426,"threshold_uncertainty_score":0.4728402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142565897978882,"score_gpt":0.2427321277509553,"score_spread":0.2284755379530671,"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."}}