{"id":"W4388870670","doi":"10.1039/d3lc00683b","title":"Digital microfluidics with distance-based detection – a new approach for nucleic acid diagnostics","year":2023,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Microfluidics; Digital microfluidics; Nucleic acid; Nucleic acid detection; Computer science; Nanotechnology; Engineering; Biology; Materials science; Electrical engineering; Genetics","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":[0.001023916,0.0006752528,0.0004776194,0.001177877,0.000360871,0.001199852,0.001542703,0.0008637741,0.002003977],"category_scores_gemma":[0.001203327,0.0005965025,0.0005264224,0.0004882546,0.00129782,0.001676926,0.001667293,0.0009093003,0.001313791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007080336,"about_ca_system_score_gemma":0.0006038253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00028297,"about_ca_topic_score_gemma":0.0006317457,"domain_scores_codex":[0.9986886,0.0001726599,0.00007804162,0.0003270354,0.0006645733,0.00006905611],"domain_scores_gemma":[0.9995126,0.0001659298,0.0001055364,0.0001015581,0.00006695233,0.00004737952],"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":[0.0001311726,0.00009684762,0.0007362774,0.0006119657,0.00005511952,0.00007627509,0.00006383302,0.0004266065,0.8675027,0.01208762,0.00242487,0.1157867],"study_design_scores_gemma":[0.00004451356,0.0004698666,0.001376892,0.00007135423,0.00005797629,0.001177818,0.00002847219,0.005469064,0.9022189,0.004731034,0.08424882,0.0001052532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09956004,0.04525357,0.8133503,0.003922406,0.004161591,0.0006554455,0.001128011,0.00325751,0.02871128],"genre_scores_gemma":[0.2815005,0.01763796,0.6783909,0.002029923,0.0009715864,0.0005105027,0.0006003725,0.0001152027,0.01824312],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002003977,"threshold_uncertainty_score":0.006703913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105631350392828,"score_gpt":0.1965556135709991,"score_spread":0.1859924785317163,"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."}}