{"id":"W2087776455","doi":"10.1115/imece2007-41329","title":"Numerical and Microfluidic-Based Cell-Sorting Devices","year":2007,"lang":"en","type":"article","venue":"","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microfluidics; Sorting; Lab-on-a-chip; Chip; Channel (broadcasting); Computer science; Flow control (data); Electrokinetic phenomena; Electronic engineering; Cell sorting; Fluidics; Reliability (semiconductor); Materials science; Nanotechnology; Engineering; Electrical engineering","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":[0.0004231288,0.000375855,0.0004195941,0.0004483838,0.0004515367,0.0008738317,0.001095633,0.000778758,0.003373196],"category_scores_gemma":[0.001008849,0.0002573915,0.0003359661,0.0005240524,0.0005311086,0.0006678922,0.0006542506,0.0004818931,0.0014394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008196087,"about_ca_system_score_gemma":0.0007827351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006695798,"about_ca_topic_score_gemma":0.0009617543,"domain_scores_codex":[0.9993655,0.00004473314,0.00004383384,0.00008261525,0.0004387065,0.00002467815],"domain_scores_gemma":[0.9997522,0.00008455737,0.00003409396,0.0000432281,0.00006860738,0.00001720258],"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":[0.0001976148,0.0001720699,0.001312829,0.001182015,0.00004111427,0.0002661982,0.000138894,0.06410841,0.6491736,0.1024571,0.007498635,0.1734515],"study_design_scores_gemma":[0.00009215475,0.0002018964,0.001949579,0.0001030734,0.00004730573,0.0005583879,0.00003084843,0.202833,0.5729692,0.01511708,0.2059749,0.0001225851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07203783,0.007224954,0.8713754,0.001813348,0.001350063,0.0005445874,0.002422468,0.003605141,0.03962627],"genre_scores_gemma":[0.2407146,0.004727378,0.7262949,0.0007385823,0.0001673941,0.0008084304,0.001149221,0.0001007819,0.02529863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003373196,"threshold_uncertainty_score":0.01128447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00806382542264789,"score_gpt":0.20429995502403,"score_spread":0.1962361296013821,"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."}}