{"id":"W7039054363","doi":"","title":"Laser oxidized Sn/In films for microlithography applications","year":2006,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simon Fraser University","keywords":"Laser; Microelectronics; Wafer; Grayscale; Etching (microfabrication); Masking (illustration); Anisotropy; Photolithography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005659527,0.0001893991,0.00009234378,0.0001076153,0.0001304316,0.0002290378,0.0001990195,0.0001316265,0.001972011],"category_scores_gemma":[0.00005355054,0.0001424354,0.00007724725,0.00007760683,0.00006927598,0.0001596082,0.0001016199,0.0002199374,0.0003257571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001843989,"about_ca_system_score_gemma":0.0001279549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005464033,"about_ca_topic_score_gemma":0.001652462,"domain_scores_codex":[0.9999633,0.000002063945,0.000001716785,0.000007223785,0.00001954781,0.000006159898],"domain_scores_gemma":[0.9999802,0.000002816373,0.000004031015,0.000002334143,0.000006443313,0.000004152425],"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":[0.000006500878,0.000002574591,0.00003294376,0.00002875662,0.000001014054,0.00001487653,0.000008185639,0.00002728762,0.9985322,0.00007179629,0.00005415924,0.001219594],"study_design_scores_gemma":[0.000003292216,0.00004798901,0.0007452944,0.000004514868,0.000005545936,0.00005437255,0.00002248037,0.000532499,0.9938275,0.00002987188,0.004724442,0.000002194449],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9751492,0.002418844,0.009530013,0.0001936853,0.0001473064,0.00005186153,0.000289931,0.0002037664,0.01201544],"genre_scores_gemma":[0.9573267,0.003058098,0.02315961,0.00007262122,0.00003011845,0.00003455027,0.0004210542,0.00006805373,0.01582921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001972011,"threshold_uncertainty_score":0.006597042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009023999341954785,"score_gpt":0.2195114080928759,"score_spread":0.2104874087509211,"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."}}