{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006393052,0.0001075828,0.0001422441,0.00005464237,0.00002386433,0.00001838552,0.00003261961,0.00006840626,0.000005481438],"category_scores_gemma":[0.00001953374,0.00009270995,0.00003300161,0.00006618565,0.00004257079,0.00001064333,0.00000877718,0.00005355848,0.000001727783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001250818,"about_ca_system_score_gemma":0.000008690677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000033485,"about_ca_topic_score_gemma":0.000003661927,"domain_scores_codex":[0.9995599,0.00001243476,0.0001242658,0.0001231767,0.00005719839,0.0001230023],"domain_scores_gemma":[0.9997259,0.00003169453,0.00001987619,0.0001119357,0.00001978512,0.00009076558],"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":[0.0004171495,0.0000774913,0.0002383937,0.0004025479,0.00003931728,0.000003575034,0.0002265971,0.0006283362,0.9754661,0.0002816712,0.000453146,0.0217657],"study_design_scores_gemma":[0.002699401,0.0008408411,0.006926415,0.0001177277,0.00008116004,0.00001223224,0.00007914918,0.1331077,0.8532822,0.0001093771,0.002409557,0.00033425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867656,0.01221023,0.0004626226,0.0001103736,0.0001044268,0.0001360218,0.00003078061,0.00004487654,0.0001351139],"genre_scores_gemma":[0.9996132,0.00006212286,0.0001463406,0.00006160929,0.0000359879,0.000007157264,0.000004742418,0.00001789629,0.00005099912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1324794,"threshold_uncertainty_score":0.3780602,"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."}}