{"id":"W2951001292","doi":"10.7150/ntno.20758","title":"Amplified visual immunosensor integrated with nanozyme for ultrasensitive detection of avian influenza virus","year":2017,"lang":"en","type":"article","venue":"Nanotheranostics","topic":"Advanced Nanomaterials in Catalysis","field":"Materials Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministry of Agriculture, Food and Rural Affairs; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Detection limit; Avian influenza virus; Immunoassay; Influenza A virus subtype H5N1; Virus; Chemistry; Analyte; Colloidal gold; Bioanalysis; Naked eye; Influenza A virus; Combinatorial chemistry; Nanotechnology; Virology; Nanoparticle; Chromatography; Materials science; Antibody; Biology","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":[0.0003237721,0.0002952564,0.0005190654,0.0001094138,0.0005295552,0.0001624964,0.0004062204,0.0001812801,0.00006460009],"category_scores_gemma":[0.001012445,0.0002384881,0.00009708943,0.0001070653,0.0005024495,0.0003218043,0.00005001757,0.00008181695,0.00003871527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000960917,"about_ca_system_score_gemma":0.00009490368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002914237,"about_ca_topic_score_gemma":0.0001805591,"domain_scores_codex":[0.9983208,0.00007506715,0.0005090133,0.0004300367,0.0002865795,0.0003785299],"domain_scores_gemma":[0.9974123,0.0004023967,0.0008055113,0.0007696887,0.0005426764,0.00006739425],"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":[0.001753373,0.0000893566,0.0001412643,0.00004128609,0.00004834156,0.000005731662,0.0002695098,0.00008793702,0.9946709,0.00007563116,0.000004737428,0.002811943],"study_design_scores_gemma":[0.00176606,0.0004910651,0.001346572,0.0001046186,0.0001030887,0.00001206945,0.0001188137,0.00011967,0.9947158,0.0002078557,0.0007052043,0.0003092342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9291438,0.00004781631,0.0688251,0.00001721307,0.0006316293,0.0006081309,0.000567825,0.00009375822,0.00006475503],"genre_scores_gemma":[0.9897341,0.00001597154,0.009761279,0.000106944,0.0001204259,0.00005528628,0.00002592058,0.0000707865,0.0001092871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06059032,"threshold_uncertainty_score":0.9725263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0190740259869833,"score_gpt":0.2996929596307992,"score_spread":0.280618933643816,"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."}}