{"id":"W3133337221","doi":"10.1016/j.sbsr.2021.100406","title":"Fast, highly sensitive and label free detection of small genetic sequence difference of DNA using novel Surface-Enhanced Raman Spectroscopy nanostructured sensor","year":2021,"lang":"en","type":"article","venue":"Sensing and Bio-Sensing Research","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; American University of Sharjah","keywords":"Raman spectroscopy; Surface-enhanced Raman spectroscopy; Biomolecule; Materials science; Nanotechnology; Nanoparticle; Isotropic etching; Analytical Chemistry (journal); Spectroscopy; Silicon; Etching (microfabrication); Optoelectronics; Chemistry; Raman scattering; Chromatography; Optics","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":[0.000514641,0.0001808123,0.0003736655,0.0001053492,0.0003905754,0.0001264361,0.00008369375,0.000116722,0.000002337772],"category_scores_gemma":[0.0002946464,0.0001621615,0.00004033779,0.0004648705,0.000719314,0.00004762903,0.0001907589,0.0001841716,0.000001131327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004554597,"about_ca_system_score_gemma":0.0001317544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008742873,"about_ca_topic_score_gemma":0.0002648747,"domain_scores_codex":[0.9979362,0.0002889491,0.000376092,0.0005509768,0.0003924103,0.0004553449],"domain_scores_gemma":[0.9982494,0.00036293,0.0001551656,0.0004177439,0.0006906221,0.0001241242],"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":[0.00005721957,0.0000371441,0.00008130172,0.00006912929,0.00001210142,0.00001220718,0.0004845632,0.00004005103,0.9912742,0.00003857116,9.640569e-7,0.007892516],"study_design_scores_gemma":[0.0004379209,0.00008802892,0.003894651,0.0002460653,0.00002997921,0.0001260438,0.0008218825,0.01536589,0.97841,0.0004098865,0.000002856733,0.000166809],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957089,0.0001694818,0.003538185,0.0001840104,0.0001006612,0.0001782299,0.00005514901,0.00002722475,0.00003817324],"genre_scores_gemma":[0.939799,0.00007507285,0.06000445,0.0000143449,0.00004860923,1.72265e-7,0.000002336256,0.00001795019,0.00003801995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05646627,"threshold_uncertainty_score":0.6612755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06935010406836595,"score_gpt":0.3093330144237676,"score_spread":0.2399829103554016,"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."}}