{"id":"W2002078626","doi":"10.1109/tuffc.2011.1896","title":"Microbubble sizing and shell characterization using flow cytometry","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"Division of Mathematical Sciences; National Institute of Biomedical Imaging and Bioengineering; Nanjing University; University of Washington","keywords":"Microbubbles; Materials science; Particle size; Population; Volumetric flow rate; Elasticity (physics); Shear modulus; Bubble; Viscosity; Mechanics; Optics; Acoustics; Ultrasound; Composite material; Physics; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001057445,0.0002402995,0.0002361427,0.000244695,0.0002707187,0.00007032766,0.00009402331,0.0001606746,0.00005561689],"category_scores_gemma":[0.000005238047,0.0002532366,0.00006014454,0.0004342893,0.00005114935,0.0002170616,3.760594e-7,0.0003154907,0.00000726057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000719629,"about_ca_system_score_gemma":0.0000310199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004325038,"about_ca_topic_score_gemma":0.00002264732,"domain_scores_codex":[0.9989946,0.00002363466,0.0002625219,0.0002721813,0.0001078625,0.0003391842],"domain_scores_gemma":[0.9994782,0.00009905862,0.00004186758,0.0001878417,0.00005808842,0.0001349709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001656067,0.0001016665,0.0003136068,0.00003584075,0.00011711,0.000002178303,0.000463397,0.001686431,0.9637376,0.00028367,0.000001977221,0.03323996],"study_design_scores_gemma":[0.002386003,0.0003139112,0.003158395,0.00007567788,0.0004759611,0.0002202684,0.00007234117,0.9027612,0.08800153,0.0009491519,0.0004409614,0.001144592],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2582674,0.00055804,0.7400373,0.00001541864,0.0001614424,0.0002474315,0.0001239445,0.0001807017,0.0004083028],"genre_scores_gemma":[0.9935238,0.001526686,0.004674939,0.0001081387,0.0000367867,0.00003576891,0.00001118665,0.00005543555,0.00002724057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9010748,"threshold_uncertainty_score":0.999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685745282742112,"score_gpt":0.1868117979105035,"score_spread":0.1699543450830824,"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."}}