{"id":"W2147209171","doi":"10.1109/memsys.2007.4432971","title":"SU-8 surface-micromachining process utilizing PMGI as a sacrificial material","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Surface micromachining; Resist; Materials science; Rapid prototyping; Process (computing); Lift (data mining); Bulk micromachining; Layer (electronics); Nanotechnology; Fabrication; Computer science; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001270083,0.0003166297,0.0002041607,0.0001246994,0.0001310572,0.000211073,0.0002617624,0.0002572231,0.0006907709],"category_scores_gemma":[0.0001408468,0.0001762878,0.0001608403,0.0001041395,0.0001989929,0.0002816173,0.000196772,0.0005541851,0.0006765131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001203066,"about_ca_system_score_gemma":0.0001752792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001005243,"about_ca_topic_score_gemma":0.0003447148,"domain_scores_codex":[0.999912,0.000007055949,0.000006228826,0.00002411682,0.00003653413,0.00001417122],"domain_scores_gemma":[0.9999177,0.00002299464,0.00002589354,0.00001629672,0.00001015819,0.000006899437],"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":[0.00001033341,0.00000543392,0.00007095286,0.00004308289,0.000002666744,0.00004632392,0.00001473332,0.00008022182,0.9941205,0.000242321,0.00008424641,0.005279084],"study_design_scores_gemma":[0.000008505162,0.0001886737,0.001071949,0.000003965941,0.000008560193,0.0005148634,0.00001322818,0.0008258884,0.9879329,0.0001554106,0.009270226,0.000005886231],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.735446,0.004383696,0.245431,0.0003873142,0.0005022709,0.0001750478,0.0003118334,0.001532084,0.01183077],"genre_scores_gemma":[0.8373898,0.001735733,0.1554202,0.00008225161,0.00008746274,0.00007535044,0.0002297306,0.00006453269,0.00491498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006907709,"threshold_uncertainty_score":0.002310812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056056743705933,"score_gpt":0.2666798226773333,"score_spread":0.256119255240274,"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."}}