{"id":"W1492396317","doi":"10.1109/cleoe.2005.1568441","title":"Laser micromachining of silicon in sulfur hexafluoride atmosphere: experiment and numerical simulation","year":2006,"lang":"en","type":"article","venue":"","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sulfur hexafluoride; Silicon; Surface micromachining; Materials science; Atmosphere (unit); Laser; Etching (microfabrication); Optoelectronics; Sulfur; Optics; Chemistry; Nanotechnology; Fabrication; Metallurgy; Meteorology","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":[0.00005715275,0.00008764692,0.0001262792,0.00001297889,0.00001042853,0.00001897991,0.00004058416,0.00004736664,0.00004079104],"category_scores_gemma":[0.000004851051,0.00008366675,0.00001161537,0.00007071665,0.00001506183,0.0001027862,0.00002148984,0.00004122482,0.000001639639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003388725,"about_ca_system_score_gemma":0.000003998066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003510465,"about_ca_topic_score_gemma":0.00001051105,"domain_scores_codex":[0.9995231,0.00001054248,0.0002036329,0.00009848847,0.00005775222,0.0001064808],"domain_scores_gemma":[0.9998484,0.00002715195,0.00001970956,0.00007840851,0.000009892055,0.00001647245],"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":[0.00001296528,0.00004456455,0.007897656,0.00008574688,0.000005450858,0.000004050948,0.0001517608,0.1345204,0.8534113,0.0001742475,0.0002041734,0.003487719],"study_design_scores_gemma":[0.0001747651,0.00001610836,0.003937375,0.00002449752,0.00000191409,8.043348e-7,0.00001271408,0.2070079,0.7883227,0.0002873183,0.0001239454,0.00009001043],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900259,0.000130731,0.00796226,0.000009032657,0.0000376669,0.00007494791,0.00000104964,0.0002813803,0.001477045],"genre_scores_gemma":[0.9934881,0.000002181937,0.006419755,0.000008984215,0.00002593762,0.000006993279,0.000003636411,0.00001861208,0.00002573735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07248744,"threshold_uncertainty_score":0.3411831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006351215414864314,"score_gpt":0.2296039418286624,"score_spread":0.2232527264137981,"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."}}