{"id":"W4385782789","doi":"10.1101/2023.08.10.552726","title":"Additive Manufacturing Leveraged Microfluidic Setup for Sample to Answer Colorimetric Detection of Pathogens","year":2023,"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","funders":"Canadian Institutes of Health Research; Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada; Mitacs; McGill University","keywords":"Microfluidics; Loop-mediated isothermal amplification; Cartridge; Computer science; Computer hardware; Proof of concept; Nanotechnology; Materials science; Chemistry; DNA","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":[0.0005057207,0.0008718902,0.0004725584,0.0005422101,0.0002811034,0.0004898239,0.0009247062,0.0007089975,0.002540637],"category_scores_gemma":[0.0007909667,0.0004490243,0.0004785595,0.0001961018,0.0002574307,0.0003568752,0.0005064457,0.000567376,0.001324065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003380389,"about_ca_system_score_gemma":0.0004660366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002284638,"about_ca_topic_score_gemma":0.0003743352,"domain_scores_codex":[0.9992255,0.00008008788,0.00007020927,0.0002480592,0.0003060363,0.00007022682],"domain_scores_gemma":[0.9994759,0.0001385358,0.0001199412,0.0001041094,0.0001298262,0.00003162771],"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":[0.00005907356,0.00004374553,0.000232541,0.0001684598,0.00001419314,0.0001504179,0.00003048936,0.0003361001,0.9912719,0.0003432801,0.0004904529,0.006859401],"study_design_scores_gemma":[0.0000130618,0.0002782306,0.001263697,0.00001185147,0.00002439011,0.0003145081,0.00001290771,0.003216324,0.988695,0.00008444987,0.006053972,0.0000316794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5882227,0.003298442,0.3874067,0.0009394858,0.001399133,0.001656328,0.003241215,0.008234479,0.005601427],"genre_scores_gemma":[0.6792433,0.001551965,0.3077636,0.0006215495,0.0002802142,0.001826948,0.001824374,0.000282611,0.006605377],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002540637,"threshold_uncertainty_score":0.008499324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729275302903722,"score_gpt":0.2102131664041272,"score_spread":0.1929204133750899,"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."}}