{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003796762,0.0004290812,0.0003674808,0.0004368615,0.0002824019,0.0004933719,0.0005685561,0.0007268511,0.000464627],"category_scores_gemma":[0.0006698581,0.0002367436,0.0002906664,0.0002302517,0.0003419438,0.0005725247,0.0003234698,0.0003402116,0.0002442966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004210937,"about_ca_system_score_gemma":0.0004025762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003956167,"about_ca_topic_score_gemma":0.0004881234,"domain_scores_codex":[0.9997169,0.00003287291,0.00002059203,0.00006809814,0.0001236099,0.00003784443],"domain_scores_gemma":[0.9997676,0.00005776098,0.00005520181,0.00002738498,0.00007081885,0.00002133477],"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":[0.00002689164,0.00002663089,0.0001469538,0.0000572511,0.000003447415,0.00003176252,0.00002108753,0.0009438215,0.9934525,0.0004336928,0.00008215401,0.004773734],"study_design_scores_gemma":[0.00003688931,0.00035842,0.0008477562,0.00001107952,0.00002094746,0.0001975436,0.00001831557,0.02518113,0.9685306,0.0001509322,0.004619008,0.00002744481],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6342767,0.002110158,0.3585868,0.000340204,0.0002550108,0.0001974855,0.0001712723,0.001320512,0.002741782],"genre_scores_gemma":[0.7774054,0.0004470809,0.2204652,0.0001072606,0.0000562461,0.0001226579,0.0001087012,0.00006180938,0.001225721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007268511,"threshold_uncertainty_score":0.003055274,"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."}}