{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000210072,0.0001986354,0.0001997622,0.0002194541,0.00008347505,0.00003328207,0.0003078767,0.0002298391,0.00004106012],"category_scores_gemma":[0.0008947511,0.0001322051,0.00006833675,0.0003810263,0.0001061761,0.0000715799,0.00004279804,0.0001281061,0.0001068573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001179046,"about_ca_system_score_gemma":0.00002210199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002639837,"about_ca_topic_score_gemma":0.00002666053,"domain_scores_codex":[0.9988831,0.00001111886,0.0002525581,0.0002814275,0.0001089338,0.000462851],"domain_scores_gemma":[0.999182,0.0003919132,0.00003104293,0.0002264859,0.00004981066,0.0001186826],"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":[0.000006236437,0.00001745923,0.00006586927,0.00003920206,0.00001843908,5.296915e-7,0.00002348631,6.008486e-8,0.7083101,0.00002354773,0.006154855,0.2853402],"study_design_scores_gemma":[0.000278248,0.0001713453,0.0002130564,0.0001047033,0.00001130957,0.000006380662,0.00003530762,0.00004405658,0.6811486,0.0002235623,0.3175971,0.0001662659],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.661225,0.002219807,0.3275017,0.002952809,0.000845192,0.0005178583,0.0004012684,0.004168002,0.0001683294],"genre_scores_gemma":[0.9934332,0.0001602019,0.005870361,0.0001294986,0.0001719238,0.00008631479,0.00002062258,0.00004731388,0.00008054479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3322082,"threshold_uncertainty_score":0.5391166,"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."}}