{"id":"W2068968026","doi":"10.1039/c4lc01468e","title":"Rapid and multiplex detection of Legionella's RNA using digital microfluidics","year":2015,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Genome Canada","keywords":"Legionella; Multiplex; Microfluidics; Digital microfluidics; Computational biology; Digital polymerase chain reaction; Biology; Bacteria; Microbiology; Nanotechnology; Genetics; Chemistry; Polymerase chain reaction; Gene; Materials science","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":[0.00004195068,0.00007260584,0.00009075182,0.00005092381,0.00001799596,0.00002421099,0.00002191525,0.00005991055,0.00000137791],"category_scores_gemma":[0.00002230914,0.00006702039,0.00002718698,0.00009473004,0.00002608104,0.00006418026,0.000008816903,0.00007622684,0.000007073198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002436221,"about_ca_system_score_gemma":0.000003266734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001497124,"about_ca_topic_score_gemma":0.000002228523,"domain_scores_codex":[0.9996486,0.000005732207,0.0001028072,0.00008035355,0.00007254446,0.00009000034],"domain_scores_gemma":[0.9998124,0.00001283272,0.00001570046,0.00007157762,0.00002194711,0.00006553957],"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":[0.00003846354,0.00002355704,0.000201893,0.00004190261,0.0000242809,0.000002460867,0.0001226492,0.0007802644,0.930733,0.00005115713,0.00007019057,0.06791023],"study_design_scores_gemma":[0.0006634413,0.0001508356,0.001332103,0.00004097337,0.0000177124,0.00001822485,0.00008829164,0.1850376,0.8070295,0.0002281078,0.005212454,0.0001807419],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962627,0.0003362837,0.002084126,0.00001174144,0.0001533429,0.00004227473,0.000005559837,0.00006973045,0.001034195],"genre_scores_gemma":[0.9997178,0.00005055907,0.00009799711,0.00001320734,0.00007370036,4.245092e-7,0.000001129752,0.00001346301,0.00003174773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1842573,"threshold_uncertainty_score":0.2733012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03009792894697116,"score_gpt":0.213368479621879,"score_spread":0.1832705506749079,"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."}}