{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003689787,0.0007214446,0.000617836,0.0003823751,0.0002426997,0.0002178809,0.0004788619,0.000464152,0.0002817923],"category_scores_gemma":[0.00007773815,0.0007172836,0.0001753226,0.0007519706,0.00008132158,0.00008608583,0.0003116905,0.001946186,0.0001040594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005030155,"about_ca_system_score_gemma":0.000129205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000451352,"about_ca_topic_score_gemma":0.000003812034,"domain_scores_codex":[0.9972257,0.00009779483,0.00050852,0.0009114924,0.0005564378,0.0007000728],"domain_scores_gemma":[0.9981131,0.0000804101,0.0001719386,0.001160723,0.0001810512,0.000292779],"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":[0.000221135,0.000483021,0.007256558,0.002948584,0.002315954,0.0007369801,0.00005899329,0.1804099,0.8002985,0.003495325,0.001728845,0.00004616216],"study_design_scores_gemma":[0.002744324,0.0007700893,0.1154121,0.002301403,0.001190592,3.807994e-7,0.00004176842,0.2127681,0.5992061,0.00001376054,0.05771653,0.007834921],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915886,0.0005810071,0.002775784,0.0001153204,0.001720168,0.0005908023,0.0001598151,0.002170639,0.0002978762],"genre_scores_gemma":[0.9965473,0.0002107508,0.00215095,0.0001610556,0.0004892169,0.0001431244,5.687698e-7,0.000281931,0.00001505096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2010924,"threshold_uncertainty_score":0.9995278,"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."}}