{"id":"W4297101535","doi":"10.1101/2022.09.23.508398","title":"3D-printed capillaric ELISA-on-a-chip with aliquoting","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":0,"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; McGill University","keywords":"Pipette; Nitrocellulose; Chromatography; Capillary action; Substrate (aquarium); Chip; Chemistry; Microfluidics; Conjugate; Microfluidic chip; Capillary electrophoresis; Pulmonary surfactant; 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":[0.0003759481,0.0007043211,0.0005455792,0.0005010886,0.0002279138,0.0005391177,0.002041746,0.001051619,0.002932363],"category_scores_gemma":[0.000626553,0.0006408222,0.0007270537,0.0002563506,0.0003147106,0.0003783658,0.0006078546,0.0007896925,0.002162317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000534486,"about_ca_system_score_gemma":0.0004064254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008138112,"about_ca_topic_score_gemma":0.001131895,"domain_scores_codex":[0.9992365,0.00006270922,0.00004716584,0.0002522393,0.0003334096,0.00006802174],"domain_scores_gemma":[0.9993238,0.0001857867,0.0001038344,0.0001719294,0.0001721427,0.00004237856],"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":[0.00004056472,0.0000680734,0.0002868352,0.0001174595,0.00002092498,0.0001448285,0.00003025259,0.0009722757,0.9840562,0.0004641559,0.001044453,0.01275407],"study_design_scores_gemma":[0.00001682508,0.0001232977,0.001082652,0.000009221607,0.00002742291,0.0002056304,0.000007042463,0.01469364,0.9742482,0.0001066745,0.009438896,0.00004051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2627851,0.001257367,0.7002723,0.0005807506,0.001129547,0.0007008705,0.00182072,0.0195629,0.01189043],"genre_scores_gemma":[0.4788693,0.0007698428,0.4999095,0.001026046,0.000185331,0.001395482,0.001415177,0.0006171245,0.01581213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002932363,"threshold_uncertainty_score":0.009809732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009427879859320027,"score_gpt":0.1921906499097679,"score_spread":0.1827627700504479,"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."}}