{"id":"W4213401054","doi":"","title":"Surface Plasmon Resonance biosensors enhanced by active mass transport","year":2019,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Surface plasmon resonance; Biosensor; Plasmon; Surface plasmon; Resonance (particle physics); Mass transport; Optoelectronics; Materials science; Nanotechnology; Physics; Nanoparticle; Atomic physics; Engineering physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004868952,0.0008600488,0.000712845,0.0003264183,0.0002943613,0.001125908,0.0009985969,0.001451208,0.002639037],"category_scores_gemma":[0.0005300099,0.0003275437,0.0004119441,0.0001949062,0.0005074991,0.001407822,0.0005652156,0.0007602629,0.001870829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004589713,"about_ca_system_score_gemma":0.0001026093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000146748,"about_ca_topic_score_gemma":0.0001706156,"domain_scores_codex":[0.9996966,0.00005579212,0.00001383231,0.00007815974,0.0001126936,0.00004288461],"domain_scores_gemma":[0.9997907,0.0000956918,0.00003758884,0.0000171021,0.00004497299,0.00001396993],"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":[0.0000610283,0.00001877973,0.00002158181,0.00007226942,0.000004302713,0.00006181502,0.00003132944,0.0001731134,0.9958357,0.0007935386,0.0001723224,0.002754321],"study_design_scores_gemma":[0.0000247653,0.0001689341,0.0001584314,0.000008652513,0.00001462674,0.0001390639,0.00001980127,0.008413248,0.9869602,0.0004549373,0.003624103,0.00001325871],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.865173,0.005009835,0.1068285,0.002070116,0.0009980339,0.0001629782,0.0001974477,0.002023439,0.01753651],"genre_scores_gemma":[0.9535456,0.002094655,0.02422659,0.000439196,0.0002970023,0.0001043204,0.0001270407,0.0002019152,0.01896353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002639037,"threshold_uncertainty_score":0.008828402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004857552062202493,"score_gpt":0.2172867341807272,"score_spread":0.2124291821185247,"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."}}