{"id":"W4318754007","doi":"10.1039/d2lc00878e","title":"3D-printed capillaric ELISA-on-a-chip with aliquoting","year":2023,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; McGill University","keywords":"Pipette; Chromatography; Nitrocellulose; Capillary action; Chip; Substrate (aquarium); Chemistry; Detection limit; Conjugate; Microfluidics; Capillary electrophoresis; Pulmonary surfactant; Reagent; Nanotechnology; Materials science; Membrane; Computer science","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":[0.0005305593,0.001049129,0.0006506193,0.0008745635,0.0004020323,0.0008069555,0.001900191,0.00159558,0.009940406],"category_scores_gemma":[0.001000769,0.0009409954,0.0008325878,0.0005487452,0.0003912989,0.0005550137,0.0007658975,0.001284526,0.007268156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004756732,"about_ca_system_score_gemma":0.0005711352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041974,"about_ca_topic_score_gemma":0.003073784,"domain_scores_codex":[0.9988365,0.00008095105,0.0000625181,0.0004532537,0.0004884799,0.00007840389],"domain_scores_gemma":[0.9992691,0.0002119176,0.00007956843,0.0001884404,0.0001963195,0.00005468481],"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":[0.00006203821,0.0001138146,0.0002662868,0.0002741497,0.00004179118,0.0001992704,0.00005590641,0.0008288305,0.9704722,0.0008605854,0.003445736,0.02337951],"study_design_scores_gemma":[0.00002686905,0.0001541288,0.001706479,0.00003476801,0.00005751957,0.0005273974,0.00002380652,0.01318375,0.9439794,0.0003784136,0.0398511,0.00007636641],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.154606,0.004916416,0.7689323,0.0008589998,0.003095301,0.001191724,0.003840494,0.02080564,0.04175315],"genre_scores_gemma":[0.359221,0.003462839,0.5579189,0.002600055,0.0003508168,0.002697725,0.004719989,0.002005643,0.06702301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009940406,"threshold_uncertainty_score":0.03325403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223828925837233,"score_gpt":0.2130509465623353,"score_spread":0.200812657303963,"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."}}