{"id":"W2903673903","doi":"10.1016/j.matpr.2018.09.054","title":"Ultrasensitive Analyte Detection by Combining Nanoparticle-based Surface-Enhanced Raman Scattering (SERS) Substrates with Multivariate Analysis","year":2018,"lang":"en","type":"article","venue":"Materials Today Proceedings","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Raman scattering; Analyte; Materials science; Nanoparticle; Microelectrode; Fractal analysis; Nanotechnology; Raman spectroscopy; Fractal dimension; Analytical Chemistry (journal); Chemistry; Electrode; Chromatography; Fractal; Optics","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006559985,0.0003132424,0.0004947464,0.0001158543,0.0005330138,0.0006239564,0.0002267184,0.00009329491,0.0005078407],"category_scores_gemma":[0.00003570239,0.0002557962,0.00007726956,0.0008263863,0.0002824532,0.0004083925,0.00004040466,0.00006216323,0.0001612486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005827426,"about_ca_system_score_gemma":0.00002589984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003536945,"about_ca_topic_score_gemma":0.00005541689,"domain_scores_codex":[0.9978775,0.00004894315,0.0005040804,0.0006857913,0.000310352,0.0005732742],"domain_scores_gemma":[0.9988605,0.00006645849,0.0003438289,0.0002127175,0.0003504669,0.0001659824],"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":[0.0002580141,0.0001052996,0.0009564256,0.0000230549,0.00008024261,9.966105e-7,0.000505109,0.0001009898,0.9977815,0.00006925536,0.0000309734,0.00008818666],"study_design_scores_gemma":[0.0006367548,0.000219689,0.003300266,0.00005195474,0.0003415796,0.000002141641,0.0004414302,0.001449566,0.9931234,0.00003229895,0.000030717,0.0003702561],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979615,0.000007426091,0.0009185059,0.0002060341,0.0001042511,0.0003233442,0.00007008603,0.0002557401,0.0001531051],"genre_scores_gemma":[0.9985346,0.000001764641,0.00108555,0.0001226359,0.00009324618,0.00006300079,0.00002055322,0.0000370048,0.00004163168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004658107,"threshold_uncertainty_score":0.9999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009499661986432165,"score_gpt":0.2273142016722782,"score_spread":0.2178145396858461,"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."}}