{"id":"W2301900151","doi":"10.1117/12.2211740","title":"Classification of biological cells using a sound wave based flow cytometer","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transducer; Ultrasound; Materials science; Laser; Polydimethylsiloxane; Continuous wave; Microfluidics; Acoustic streaming; Ultrasonic sensor; Photoacoustic imaging in biomedicine; SIGNAL (programming language); Cytometry; Optics; Biomedical engineering; Flow cytometry; Acoustics; Physics; Nanotechnology; Medicine; Computer science","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":[0.001147549,0.0005783205,0.000706304,0.002601982,0.0007955214,0.001219033,0.001023025,0.001094484,0.002869567],"category_scores_gemma":[0.001055051,0.0003035158,0.0003547492,0.0009612307,0.0005963999,0.0007717409,0.0005297372,0.001060014,0.001748587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005980945,"about_ca_system_score_gemma":0.0003797908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003731318,"about_ca_topic_score_gemma":0.0006250136,"domain_scores_codex":[0.9986393,0.000136529,0.0001599197,0.0003897258,0.0006060297,0.00006856199],"domain_scores_gemma":[0.9990103,0.0004001207,0.00009829958,0.0001121252,0.0003041541,0.00007502976],"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":[0.0001350714,0.00009196948,0.001861114,0.0001155196,0.00000924942,0.00005667199,0.0000913729,0.0005306779,0.9665788,0.0007987606,0.0005782947,0.02915253],"study_design_scores_gemma":[0.00005085172,0.0005648236,0.01339704,0.00004638163,0.00007064899,0.0006213,0.0001280645,0.06744687,0.8989369,0.001452214,0.01719219,0.00009261701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2667721,0.002205253,0.7162284,0.0005973569,0.0006998914,0.001034408,0.002193671,0.00472847,0.005540344],"genre_scores_gemma":[0.2009194,0.001275472,0.7858298,0.0006491113,0.000324428,0.002035776,0.001793365,0.0001249901,0.007047672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002869567,"threshold_uncertainty_score":0.009599686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586235979844651,"score_gpt":0.2318810638454577,"score_spread":0.2060187040470112,"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."}}