{"id":"W4380901791","doi":"10.1039/d3lc00125c","title":"A competitive, bead-based assay combined with microfluidics for multiplexed toxin detection","year":2023,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Centre for Bioengineering and Biotechnology, University of Waterloo; University of Waterloo; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Microfluidics; Bead; Multiplexing; Magnetic bead; Toxin; Chromatography; Nanotechnology; Chemistry; Materials science; Engineering; Biochemistry; Electronic engineering","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":[0.001149756,0.001223325,0.000864107,0.001173678,0.000504529,0.000688064,0.001095228,0.001259253,0.001477287],"category_scores_gemma":[0.0009519976,0.000627464,0.0007512405,0.0007309093,0.0004246615,0.0005529628,0.0008722075,0.001022849,0.001085667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008382557,"about_ca_system_score_gemma":0.0009161408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001719498,"about_ca_topic_score_gemma":0.005111985,"domain_scores_codex":[0.9983497,0.0002509465,0.0001194663,0.0004516783,0.0006391987,0.0001889752],"domain_scores_gemma":[0.999592,0.0001492208,0.00005218563,0.00004923625,0.00009600639,0.00006135514],"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":[0.00006546541,0.00008626062,0.0004597073,0.0001443422,0.0000357591,0.00004933984,0.00002164351,0.000230081,0.9876391,0.0004209558,0.0003506195,0.01049667],"study_design_scores_gemma":[0.00003043183,0.0006036065,0.001966821,0.00001231057,0.00006506485,0.0003867786,0.00001213322,0.01334251,0.9778149,0.0001365906,0.005559186,0.00006981957],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3214692,0.009478929,0.6535901,0.0008906911,0.001051386,0.001902024,0.002333694,0.002313616,0.00697042],"genre_scores_gemma":[0.5422276,0.002634094,0.4431099,0.0007337114,0.000200954,0.001383687,0.00166652,0.00007903875,0.007964483],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001719498,"threshold_uncertainty_score":0.006081939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01496268970705325,"score_gpt":0.2341421265577187,"score_spread":0.2191794368506654,"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."}}