{"id":"W1892267647","doi":"10.1039/c5lc00852b","title":"Polymer-based microfluidic chip for rapid and efficient immunomagnetic capture and release of Listeria monocytogenes","year":2015,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Institut National de la Recherche Scientifique; Health Canada; National Research Council Canada","funders":"National Research Council Canada; Health Canada","keywords":"Microfluidics; Listeria monocytogenes; Immunomagnetic separation; Polymer; Magnetic nanoparticles; Magnetic separation; Microfluidic chip; Chromatography; Materials science; Nanotechnology; Listeria; Recovery rate; Chemistry; Nanoparticle; Bacteria; Biology","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":[0.0003056163,0.000524948,0.0004092525,0.0003598754,0.0002383669,0.0002770757,0.000812006,0.0005488675,0.001032528],"category_scores_gemma":[0.0002815827,0.0003045555,0.000392061,0.0001629849,0.0001678799,0.0002789491,0.0003890943,0.0003782866,0.0005720172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004717831,"about_ca_system_score_gemma":0.0005488377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004343657,"about_ca_topic_score_gemma":0.000931639,"domain_scores_codex":[0.9997409,0.00002316766,0.00002179431,0.00009135956,0.00008204873,0.00004079191],"domain_scores_gemma":[0.9998679,0.00004405155,0.00003135548,0.00001559,0.0000251981,0.00001590179],"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":[0.000060305,0.00005067001,0.0002593202,0.0001522377,0.00001679122,0.00004724104,0.00001644381,0.0004157285,0.9859956,0.0003077631,0.0005018528,0.01217601],"study_design_scores_gemma":[0.00002532465,0.0002602858,0.001814103,0.00001135156,0.0000324703,0.0001885908,0.000007022484,0.007542844,0.9821451,0.0000628719,0.007880197,0.00002992235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6848944,0.0122023,0.2829063,0.0009938782,0.001147741,0.0006740954,0.002291209,0.007481114,0.007408952],"genre_scores_gemma":[0.7055983,0.003326949,0.2827027,0.0005813537,0.0001497651,0.000653955,0.001239477,0.0001002117,0.00564734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001032528,"threshold_uncertainty_score":0.003454149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893035151750135,"score_gpt":0.2166518713404832,"score_spread":0.1977215198229819,"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."}}