{"id":"W2475080029","doi":"10.1021/acs.analchem.5b03085","title":"Microfluidic Integration of a Cloth-Based Hybridization Array System (CHAS) for Rapid, Colorimetric Detection of Enterohemorrhagic <i>Escherichia coli</i> (EHEC) Using an Articulated, Centrifugal Platform","year":2015,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Health Canada; Canadian Food Inspection Agency; National Research Council Canada","funders":"Government of Canada","keywords":"Microfluidics; Chip; Multiplex; Microfluidic chip; Chemistry; Nanotechnology; Escherichia coli; DNA; Centrifugal force; Centrifuge; Computer science; Gene; Materials science; Rotational speed; Physics; Bioinformatics; 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":[0.0002409732,0.0002037976,0.000374599,0.0001159201,0.00004016918,0.00002670978,0.00009497372,0.000228497,0.000008337114],"category_scores_gemma":[0.0001423688,0.0001994138,0.0001628105,0.0007252641,0.00006796941,0.0001382954,0.000007852748,0.0001570477,0.000001829346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002932455,"about_ca_system_score_gemma":0.00005662878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004140449,"about_ca_topic_score_gemma":0.000001858392,"domain_scores_codex":[0.9986563,0.00001942184,0.0005855336,0.0002349016,0.0002515461,0.0002523476],"domain_scores_gemma":[0.9990546,0.00005697723,0.0001428448,0.0002080745,0.0003373438,0.000200169],"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":[0.0001508902,0.0001026934,0.00005251642,0.0005144661,0.00005469469,0.000001290966,0.00001740579,0.004559044,0.9940722,0.00001742897,0.00003687128,0.0004204727],"study_design_scores_gemma":[0.0005222667,0.00008468137,0.00001768449,0.00004690815,0.0001228113,0.000004871511,0.00009970163,0.453639,0.5452893,0.00001012915,0.00006007805,0.000102542],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6907489,0.0002336883,0.3085039,0.000004876186,0.000109515,0.0001621631,0.00002487943,0.00009028016,0.0001217528],"genre_scores_gemma":[0.998741,0.00001565971,0.001005534,0.00001022061,0.0001185097,0.00000818414,0.00005825637,0.00003262196,0.000009968542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.44908,"threshold_uncertainty_score":0.813186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03028472152167692,"score_gpt":0.2345643254598788,"score_spread":0.2042796039382019,"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."}}