{"id":"W2531715055","doi":"10.1063/1.4964717","title":"Surface micromachining of polydimethylsiloxane for microfluidics applications","year":2016,"lang":"en","type":"article","venue":"Biomicrofluidics","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Electrical, Communications and Cyber Systems; National Institute of Allergy and Infectious Diseases; National Heart, Lung, and Blood Institute; New York University; Division of Chemical, Bioengineering, Environmental, and Transport Systems; York University; American Heart Association; Division of Civil, Mechanical and Manufacturing Innovation; National Institutes of Health; National Science Foundation","keywords":"Polydimethylsiloxane; Photoresist; Materials science; Surface micromachining; Reactive-ion etching; Photolithography; Microfluidics; Nanotechnology; Etching (microfabrication); Plasma etching; Optoelectronics; Fabrication; Layer (electronics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002611555,0.0002927545,0.0003663592,0.0001325119,0.0001300484,0.00001765423,0.0004318152,0.0001979564,0.00005641155],"category_scores_gemma":[0.00001646976,0.0002437776,0.0001967221,0.0003717442,0.000186819,0.00008471833,0.00004775772,0.00007702951,0.00006966558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001152794,"about_ca_system_score_gemma":0.00006700162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006746116,"about_ca_topic_score_gemma":2.33169e-7,"domain_scores_codex":[0.9984068,0.00002506726,0.0005967066,0.0003513171,0.000133911,0.0004861606],"domain_scores_gemma":[0.9989206,0.0002311604,0.0001000978,0.0004958654,0.0001170484,0.0001352305],"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":[0.00001762107,0.00003843614,0.0001425588,0.00007665329,0.00007921794,1.554664e-7,0.00003182915,4.089157e-7,0.8703431,0.003687511,0.1155398,0.01004262],"study_design_scores_gemma":[0.0004329998,0.00002951621,0.00004718312,0.00002098865,0.00003611691,0.000006614148,0.000012903,0.00001047445,0.6186517,0.0004708513,0.3800762,0.0002044679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4112863,0.1982489,0.3865707,0.0004600103,0.000194646,0.001387429,0.0009250965,0.0004866939,0.0004403112],"genre_scores_gemma":[0.7939138,0.199668,0.004709852,0.0001424785,0.0002762311,0.0003544638,0.0001007289,0.0002131131,0.0006212763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3826276,"threshold_uncertainty_score":0.9940962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101405265012655,"score_gpt":0.2242395459822749,"score_spread":0.2140990194810094,"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."}}