{"id":"W2365865181","doi":"10.1007/s10544-016-0069-8","title":"Integrated sample-to-detection chip for nucleic acid test assays","year":2016,"lang":"en","type":"article","venue":"Biomedical Microdevices","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Provincial Laboratory of Public Health","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Nucleic acid; Microfluidics; Lab-on-a-chip; Chip; Nucleic acid methods; Nanotechnology; Computer science; Materials science; Chemistry","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":[0.0006434479,0.0008885823,0.0008145304,0.0006618791,0.0004087531,0.0008771921,0.002253867,0.001335929,0.003029837],"category_scores_gemma":[0.0007605524,0.0006933358,0.0004753012,0.0003824271,0.0003190098,0.0009533896,0.0008314525,0.0009309775,0.00217182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113244,"about_ca_system_score_gemma":0.001065319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008373217,"about_ca_topic_score_gemma":0.002370422,"domain_scores_codex":[0.999071,0.00007139764,0.00003891222,0.0002404416,0.0004653791,0.000112778],"domain_scores_gemma":[0.9994553,0.0001346315,0.00005660039,0.00007343071,0.0002097469,0.00007043764],"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":[0.0001198883,0.0001567393,0.0004200847,0.0001417917,0.00005114923,0.00006050019,0.00002900202,0.0005233366,0.9847067,0.0008331031,0.001237386,0.01172027],"study_design_scores_gemma":[0.0000147944,0.0001370203,0.0008170293,0.000007891986,0.00002990175,0.000071841,0.000008055403,0.00844446,0.9841187,0.0001243907,0.006211279,0.00001461129],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3315427,0.006986453,0.6357036,0.001019001,0.001645251,0.00115592,0.003022621,0.007781883,0.01114242],"genre_scores_gemma":[0.5405546,0.002207354,0.4285253,0.00180767,0.0002998186,0.001205803,0.002682157,0.0003781379,0.02233912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003029837,"threshold_uncertainty_score":0.01013577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008804085725514905,"score_gpt":0.2159964596448627,"score_spread":0.2071923739193478,"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."}}