{"id":"W2764226061","doi":"10.3390/mi8100308","title":"A Fluidic Interface with High Flow Uniformity for Reusable Large Area Resonant Biosensors","year":2017,"lang":"en","type":"article","venue":"Micromachines","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Agence Nationale de la Recherche","keywords":"Miniaturization; Fluidics; Finite element method; Biosensor; Materials science; Interface (matter); Fabrication; Particle image velocimetry; Nanotechnology; Microfluidics; Flow (mathematics); Electronic engineering; Acoustics; Optoelectronics; Mechanical engineering; Engineering; Electrical engineering; Contact angle; Mechanics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001684373,0.0002824568,0.0003034225,0.00008527648,0.0004701358,0.000140273,0.0005139194,0.0001659361,0.00001667611],"category_scores_gemma":[0.00009452246,0.0001997163,0.00007051628,0.00006457855,0.0001491695,0.0001463632,0.0001568565,0.0001729386,0.00002562218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005065052,"about_ca_system_score_gemma":0.00001601128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001318648,"about_ca_topic_score_gemma":0.0001767957,"domain_scores_codex":[0.9989679,0.000008758157,0.0001974789,0.0002815661,0.00008560598,0.0004586264],"domain_scores_gemma":[0.9989296,0.00003378504,0.00006541185,0.0008628771,0.00005795366,0.00005041539],"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":[0.0001042636,0.00006502495,0.004162136,0.000192047,0.000118276,0.00003143961,0.0001534494,0.00005321937,0.9280455,0.0002611778,0.05691681,0.009896686],"study_design_scores_gemma":[0.00133874,0.000177273,0.003685384,0.0002173647,0.0000529017,0.0000640424,0.000103738,0.0146902,0.896718,0.0005702787,0.08181991,0.0005621683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825075,0.001806915,0.01309063,0.000553373,0.0003081607,0.0002965846,0.0002509002,0.0009111536,0.0002747884],"genre_scores_gemma":[0.9835814,0.0002673781,0.01524183,0.00002674064,0.00005426278,0.0000130725,0.00003067362,0.00005506541,0.0007295667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03132747,"threshold_uncertainty_score":0.8144194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205184053348558,"score_gpt":0.2255874357194565,"score_spread":0.2135355951859709,"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."}}