{"id":"W2889453895","doi":"10.4028/www.scientific.net/ssp.282.13","title":"Surface Recombination Velocity Imaging of HF-Etched Si Wafers Using Dynamic Heterodyne Lock-In Carrierography","year":2018,"lang":"en","type":"article","venue":"Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena","topic":"Silicon and Solar Cell Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Wafer; Heterodyne (poetry); Materials science; Passivation; Etching (microfabrication); Hydrofluoric acid; Optoelectronics; Optics; Fabrication; Isotropic etching; Nanotechnology; Acoustics; Physics","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":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.002029132,0.001387118,0.001870679,0.001082417,0.0005930195,0.000455118,0.002375591,0.0002232344,0.00009180852],"category_scores_gemma":[0.0001904799,0.001450109,0.0002062005,0.001664814,0.001058842,0.002114135,0.002794494,0.0009917394,0.0000560963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746144,"about_ca_system_score_gemma":0.0001700858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005702197,"about_ca_topic_score_gemma":0.001287064,"domain_scores_codex":[0.9918005,0.0004481931,0.002270159,0.00232752,0.0008990002,0.00225465],"domain_scores_gemma":[0.9940151,0.0003153732,0.000656085,0.004085161,0.0003074664,0.0006208226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004417307,0.005406713,0.09392392,0.006805045,0.006029031,0.0006991822,0.06765914,0.1457594,0.3632607,0.0002346929,0.01061919,0.2951857],"study_design_scores_gemma":[0.005582712,0.0004335492,0.006694932,0.0003894767,0.0002281833,0.00003352356,0.003617387,0.9637385,0.006533888,0.002916145,0.007163628,0.002668087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715592,0.00188578,0.008180697,0.00008290894,0.00121792,0.001340026,0.01437695,0.0009237436,0.0004328017],"genre_scores_gemma":[0.9807648,0.008819627,0.001568304,0.0001322478,0.0001107499,0.00003827842,0.008203579,0.0002867143,0.0000756962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8179791,"threshold_uncertainty_score":0.9998879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941868520885397,"score_gpt":0.2913038909927155,"score_spread":0.2618852057838615,"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."}}