{"id":"W3043046788","doi":"10.1039/d0pp00145g","title":"In flow metal-enhanced fluorescence for biolabelling and biodetection","year":2020,"lang":"en","type":"article","venue":"Photochemical & Photobiological Sciences","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Universidad Nacional de Córdoba","keywords":"Fluorescence; Fluorophore; Fluorescence microscope; Materials science; Microscopy; Rhodamine; Analytical Chemistry (journal); Nanoparticle; Bacteria; Chemistry; Nanotechnology; Chromatography; Optics; Physics; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001673607,0.0001380446,0.0002035461,0.00003304801,0.00008656292,0.0000395438,0.0001363803,0.0001286481,0.00004929274],"category_scores_gemma":[0.000192152,0.00009826425,0.00005864372,0.00044588,0.0002695945,0.0001040791,0.00003083367,0.0001611863,0.000007775489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001973811,"about_ca_system_score_gemma":0.000004498312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008542077,"about_ca_topic_score_gemma":0.000001793286,"domain_scores_codex":[0.9990201,0.00001587648,0.0002087162,0.000373944,0.00008505844,0.0002963008],"domain_scores_gemma":[0.9996614,0.0001282996,0.00001926693,0.00004475434,0.00001629918,0.000130012],"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":[0.00002288471,0.000009708653,0.00003495431,0.00002017705,0.000003355328,4.661895e-7,0.00002594496,0.0002712168,0.9971827,0.00003161711,0.00003842943,0.002358581],"study_design_scores_gemma":[0.0001346089,0.0001459375,0.00003873918,0.000009392335,0.000003738932,0.00000111432,0.00002049602,0.3332146,0.6651743,0.0008699644,0.000269155,0.0001179862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939848,0.0001566351,0.004648646,0.000374182,0.00009256241,0.0003691507,0.00001352413,0.0001520721,0.000208395],"genre_scores_gemma":[0.9947962,0.0001184855,0.004664707,0.0002688637,0.00007795441,0.00006373936,0.000002264739,0.000005117979,0.000002644402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3329434,"threshold_uncertainty_score":0.40071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03090387254429569,"score_gpt":0.2449555211065823,"score_spread":0.2140516485622866,"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."}}