{"id":"W4400868327","doi":"10.53063/synsint.2024.42196","title":"A surface plasmon resonance biosensor for bacteria and virus detection: A Comsol Multiphysics simulation","year":2024,"lang":"en","type":"article","venue":"Synthesis and Sintering","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiphysics; Biosensor; Surface plasmon resonance; Resonance (particle physics); Materials science; Physics; Nanotechnology; Computer science; Finite element method; Nanoparticle; Particle physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005104367,0.00008912622,0.00007881221,0.0000134818,0.00008953871,0.00005453316,0.00002563522,0.00005949621,6.771942e-7],"category_scores_gemma":[0.00003143012,0.00008336494,0.00003246561,0.00002979446,0.0000406389,0.000005608416,0.00003901828,0.00002946308,4.605172e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006880211,"about_ca_system_score_gemma":0.000004383172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005467761,"about_ca_topic_score_gemma":0.00001371679,"domain_scores_codex":[0.9995389,0.000009183434,0.00009266419,0.0002427342,0.00002406695,0.00009246218],"domain_scores_gemma":[0.9997698,0.00005977237,0.0000210262,0.000102456,0.00002128117,0.00002568562],"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":[0.00003941847,0.000006048811,0.00000833897,0.0000355116,0.000009094766,3.749927e-7,0.00001869408,0.00006801242,0.9294717,0.00005010238,0.00001186311,0.07028086],"study_design_scores_gemma":[0.00005271789,0.00005640614,0.0001314203,0.0000770165,0.00001151796,0.000007755822,0.00001766979,0.04300774,0.9077734,0.0001011029,0.04865516,0.0001080437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144941,0.0005711073,0.08453644,0.00007842462,0.00004362157,0.0001628884,0.00004746858,0.00004572019,0.0000202412],"genre_scores_gemma":[0.9890503,0.0002587825,0.01048868,0.00002006892,0.00007385531,0.00002259243,0.000006078944,0.00001812879,0.00006149544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07455623,"threshold_uncertainty_score":0.3399523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01661709386796586,"score_gpt":0.288454789078768,"score_spread":0.2718376952108022,"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."}}