{"id":"W2003420320","doi":"10.1088/0960-1317/19/6/065015","title":"Solving the shrinkage-induced PDMS alignment registration issue in multilayer soft lithography","year":2009,"lang":"en","type":"article","venue":"Journal of Micromechanics and Microengineering","topic":"Nanofabrication and Lithography Techniques","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fabrication; Polydimethylsiloxane; Materials science; Soft lithography; Lithography; Microfabrication; Photolithography; Optoelectronics; Nanotechnology; Shrinkage; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006352878,0.0005289241,0.0002961462,0.0002301496,0.0002699273,0.0003730493,0.0003613885,0.0003136467,0.0006480403],"category_scores_gemma":[0.001220939,0.000490053,0.0002671375,0.0002498969,0.0003784071,0.0006724903,0.0006939598,0.0007555374,0.000382991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002497547,"about_ca_system_score_gemma":0.0002788183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002944399,"about_ca_topic_score_gemma":0.0009329368,"domain_scores_codex":[0.9995428,0.00006344543,0.00004365263,0.00007643059,0.0002107738,0.00006287261],"domain_scores_gemma":[0.9988647,0.0004423703,0.0003584099,0.0002012743,0.0001000239,0.00003332803],"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":[0.00001907534,0.000009918606,0.0002374931,0.000065997,0.00000593021,0.00007118897,0.00004949155,0.0005605638,0.9913545,0.0002691226,0.00007121429,0.007285497],"study_design_scores_gemma":[0.000006160521,0.00008808375,0.0007994977,0.00000511328,0.000007586211,0.0001686372,0.00001612262,0.004099868,0.9929919,0.0001051908,0.00170358,0.000008181158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7480191,0.001798784,0.2461113,0.0002750636,0.0001931279,0.0001115076,0.0001159362,0.0006337427,0.002741353],"genre_scores_gemma":[0.8559189,0.001451178,0.1393453,0.00008849171,0.00004974228,0.0000844836,0.0001445218,0.0001255795,0.002791764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006480403,"threshold_uncertainty_score":0.003359735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005819313422763274,"score_gpt":0.2086785051545058,"score_spread":0.2028591917317425,"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."}}