{"id":"W4380446965","doi":"10.1088/1361-6439/acddf1","title":"A novel approach to determining the hydrodynamic resistance of droplets in microchannels using active control and grey-box system identification","year":2023,"lang":"en","type":"article","venue":"Journal of Micromechanics and Microengineering","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rule of thumb; Identification (biology); Microfluidics; Flow resistance; Variety (cybernetics); Computer science; Mechanics; Nanotechnology; Biological system; Flow (mathematics); Mechanical engineering; Biochemical engineering; Materials science; Engineering; Artificial intelligence; Algorithm; Physics","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":[0.0008771327,0.0005172549,0.0004326459,0.0005482012,0.0002316981,0.0005520112,0.0009678875,0.0004706124,0.001206512],"category_scores_gemma":[0.0009774566,0.0002663042,0.0002757674,0.0002449973,0.0006081568,0.0006931796,0.0005630916,0.0005528097,0.0002958849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004219124,"about_ca_system_score_gemma":0.0004532274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004828877,"about_ca_topic_score_gemma":0.0008543367,"domain_scores_codex":[0.9993103,0.00009032389,0.00003613157,0.0001973587,0.0003326421,0.00003331769],"domain_scores_gemma":[0.9993388,0.0003239812,0.0001039279,0.0001001387,0.0001125914,0.00002060235],"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":[0.000132496,0.0001272165,0.001010897,0.0002687093,0.00002750041,0.00007249677,0.000199914,0.0091088,0.921771,0.003716534,0.0002544358,0.06330986],"study_design_scores_gemma":[0.00002147368,0.0003245851,0.001274831,0.00001482198,0.00001776913,0.00009134877,0.00002720569,0.2709847,0.7240964,0.0008887445,0.002208159,0.00004992104],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1005978,0.0002591457,0.8957016,0.0000982097,0.00007075344,0.0001951642,0.0001030288,0.001494866,0.001479425],"genre_scores_gemma":[0.5945202,0.0001770395,0.402931,0.00007402366,0.00002076254,0.0002404784,0.00006954424,0.00005631477,0.001910552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001206512,"threshold_uncertainty_score":0.004638731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01017487019963745,"score_gpt":0.2124172534016423,"score_spread":0.2022423832020048,"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."}}