{"id":"W4200620446","doi":"10.1109/biocas49922.2021.9644950","title":"Finite Element Simulation of a Microdroplet Generation System for an Implantable Liquid Sampling Probe","year":2021,"lang":"en","type":"article","venue":"2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"","keywords":"Microfluidics; Generator (circuit theory); Sampling (signal processing); Software; Computer science; Measure (data warehouse); Finite element method; Fluent; Multiphysics; Mechanical engineering; Simulation; Engineering; Nanotechnology; Computer simulation; Materials science; Physics","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":[0.0006259507,0.0002026352,0.0003964581,0.0001486717,0.0001042159,0.00009215566,0.0001042751,0.000211251,0.00001473552],"category_scores_gemma":[0.00004459182,0.0001957519,0.00004116269,0.0003824444,0.00006411779,0.0001553517,0.00002148185,0.0001124339,0.000002262032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001102931,"about_ca_system_score_gemma":0.0001416797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002845696,"about_ca_topic_score_gemma":0.000002958624,"domain_scores_codex":[0.9983248,0.00005454891,0.0007587718,0.0003382418,0.0002460555,0.0002775718],"domain_scores_gemma":[0.9988088,0.00007025225,0.0001465512,0.0002469773,0.000643381,0.0000840615],"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":[0.000009938576,0.00003739186,0.00001225674,0.001104436,0.00005606418,0.000002372033,0.0002793831,0.0008777321,0.9817451,0.006708721,0.000624506,0.008542136],"study_design_scores_gemma":[0.0006705643,0.0003480914,0.00001221755,0.0005036801,0.00004685016,0.00005417929,0.0008396215,0.488023,0.4942676,0.00003068976,0.01485925,0.0003442708],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08362692,0.0004957755,0.9137741,0.00001241392,0.000816067,0.0005581831,0.0003471686,0.0001012073,0.0002681712],"genre_scores_gemma":[0.9976897,0.00003590617,0.0005017776,0.00001859841,0.0004029501,0.0001117807,0.001159372,0.00002702687,0.00005287068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9140628,"threshold_uncertainty_score":0.7982529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0770847751573548,"score_gpt":0.2882861031824874,"score_spread":0.2112013280251326,"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."}}