{"id":"W4386029085","doi":"10.1101/2023.08.17.553741","title":"Additively manufactured multiplexed electrochemical device (AMMED) for portable sample-to-answer detection","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; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Potentiostat; Cleanroom; Multiplex; Multiplexing; Computer science; Computer hardware; Microfluidics; Biosensor; Chip; Fluidics; Lab-on-a-chip; Embedded system; Materials science; Nanotechnology; Chemistry; Engineering; Electrical engineering; Bioinformatics; Electrochemistry; Electrode; Telecommunications","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":[0.0002874605,0.000677401,0.0006465377,0.0003937323,0.0001558914,0.0001935405,0.0003584309,0.0009080929,0.00003880157],"category_scores_gemma":[0.0005533332,0.0007614776,0.0002997722,0.0005904029,0.00003963921,0.000107881,0.0001509378,0.0009068055,0.0001058761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004155526,"about_ca_system_score_gemma":0.0001517663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006569921,"about_ca_topic_score_gemma":0.0000332237,"domain_scores_codex":[0.997179,0.00003627937,0.0005841206,0.0009993778,0.0003282159,0.0008730342],"domain_scores_gemma":[0.9981295,0.0002114409,0.0001358485,0.0006914528,0.0003997281,0.0004320512],"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":[0.00005569201,0.00004409891,0.00004898255,0.0005105572,0.0002111688,0.000005356705,0.000002525494,0.0008595268,0.9971861,0.00006027828,0.000981618,0.00003406158],"study_design_scores_gemma":[0.0003543688,0.00005943091,0.006493232,0.0002315069,0.0001612727,1.858099e-8,0.000001964253,0.01751197,0.9463727,0.00001792608,0.02787416,0.0009213852],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5677014,0.0005611767,0.4113545,0.0002277691,0.006034504,0.004089715,0.002987608,0.007015557,0.00002777951],"genre_scores_gemma":[0.984013,0.00007684266,0.01343362,0.0001811764,0.001084929,0.0008464233,0.000004781752,0.0003353178,0.00002395386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4163116,"threshold_uncertainty_score":0.9994836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665983917566631,"score_gpt":0.217174522990881,"score_spread":0.2005146838152147,"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."}}