{"id":"W2013595123","doi":"10.1116/1.4831769","title":"Stitching error reduction in electron beam lithography with <i>in-situ</i> feedback using self-developing resist","year":2013,"lang":"en","type":"article","venue":"Journal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena","topic":"Advancements in Photolithography Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Industry Canada","keywords":"Image stitching; Resist; Lithography; Optics; Electron-beam lithography; Computer science; Depth of field; Photomask; Photolithography; Materials science; Nanotechnology; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001586064,0.0003309039,0.0005307258,0.003280672,0.000307415,0.0001369708,0.000444212,0.000295962,0.000001307659],"category_scores_gemma":[0.00002600777,0.0002918123,0.00002259573,0.002639652,0.0006734244,0.0009420309,0.000091834,0.0006889297,2.043078e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006050157,"about_ca_system_score_gemma":0.0003302856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000891148,"about_ca_topic_score_gemma":0.00002104742,"domain_scores_codex":[0.9976518,0.00003198149,0.0007394611,0.0004109731,0.0003188087,0.000846938],"domain_scores_gemma":[0.9990431,0.000008364904,0.0003891543,0.000200104,0.0003048984,0.00005436116],"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":[0.00004509465,0.00005105654,0.000728603,0.0001146003,0.00002884485,0.000005069385,0.0001877007,0.00003124129,0.9870627,0.0005088204,0.000001918691,0.01123438],"study_design_scores_gemma":[0.0007420799,0.0004020556,0.0005921177,0.0006230213,0.00003648575,0.0004379484,0.0003388625,0.00008058052,0.9839731,0.01228871,0.0001338538,0.0003512215],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841117,0.01070382,0.004054053,0.0003137574,0.000112829,0.0004121656,5.241341e-7,0.0002632327,0.00002792703],"genre_scores_gemma":[0.967793,0.002143596,0.02995402,0.00001785258,0.00002197548,0.00003708162,3.357742e-7,0.00003135946,8.155615e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02589997,"threshold_uncertainty_score":0.9999534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009103309741748512,"score_gpt":0.2272106383982981,"score_spread":0.2181073286565496,"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."}}