{"id":"W2051017609","doi":"10.1117/12.746953","title":"Use of layout automation and design-based metrology for defect test mask design and verification","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advancements in Photolithography Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"Bundesministerium für Bildung und Forschung","keywords":"Reticle; Metrology; Critical dimension; Wafer; Computer science; Optical proximity correction; Software; Lithography; Automation; Dimension (graph theory); Dimensional metrology; Electronic design automation; Engineering drawing; Electronic engineering; Materials science; Embedded system; Optics; Engineering; Mechanical engineering; Nanotechnology; Optoelectronics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009860584,0.0002453433,0.0003259214,0.0001915226,0.00004933398,0.00004750314,0.0002763828,0.0001835864,0.000001433906],"category_scores_gemma":[0.0007384152,0.0002287955,0.0002318,0.0002455002,0.0002065084,0.0004334277,0.00003898705,0.0001449321,6.26046e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009074274,"about_ca_system_score_gemma":0.00001218048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003007131,"about_ca_topic_score_gemma":7.25562e-8,"domain_scores_codex":[0.9985922,2.920998e-8,0.0005795604,0.0002596977,0.0002838051,0.000284726],"domain_scores_gemma":[0.998081,0.0008088151,0.0002529962,0.0000509837,0.0007329236,0.00007328979],"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":[0.0001668386,0.00007673758,0.001238671,0.0008424394,0.0002888383,3.824459e-8,0.0001256639,0.002781824,0.9160222,0.07684845,0.0003672405,0.001241106],"study_design_scores_gemma":[0.0006914661,0.0005050303,0.001727483,0.0001532481,0.000164447,0.000005635233,0.0001395224,0.3447604,0.6495555,0.00163245,0.0004251556,0.0002396053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8268864,0.0001144179,0.1716,0.00009845228,0.00006474845,0.0009829089,0.00003551224,0.0001601297,0.00005746086],"genre_scores_gemma":[0.4471881,0.00005773745,0.5524995,0.00001835077,0.00003429841,0.0001548049,0.000004615954,0.00003774679,0.00000485208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3808995,"threshold_uncertainty_score":0.9330009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104922124087828,"score_gpt":0.2479071473919973,"score_spread":0.226857926151119,"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."}}