{"id":"W1585562448","doi":"10.1002/jmr.2172","title":"Increasing throughput of surface plasmon resonance–based biosensors by multiple analyte injections","year":2012,"lang":"en","type":"article","venue":"Journal of Molecular Recognition","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Surface plasmon resonance; Analyte; Biosensor; Biomolecule; Throughput; Kinetic energy; Biological system; Response surface methodology; Surface plasmon; Resonance (particle physics); Computer science; Nanotechnology; Chemistry; Plasmon; Materials science; Chromatography; Nanoparticle; Optoelectronics; Physics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005522727,0.002204201,0.003661093,0.001908813,0.0005596707,0.00205637,0.00289984,0.002271491,0.001927733],"category_scores_gemma":[0.004772014,0.001359625,0.001659428,0.001382034,0.0008643657,0.002063363,0.001901636,0.002836349,0.002357179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001160693,"about_ca_system_score_gemma":0.000762675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000513786,"about_ca_topic_score_gemma":0.000749674,"domain_scores_codex":[0.9947495,0.0009744886,0.0003626067,0.001489708,0.001978558,0.0004451704],"domain_scores_gemma":[0.9956849,0.002349661,0.000345392,0.0005179901,0.0008945451,0.0002074504],"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":[0.0001591052,0.0001494993,0.000234085,0.0001098272,0.00002849953,0.00004274974,0.0000808521,0.001416066,0.9847001,0.000229358,0.0002097672,0.01264016],"study_design_scores_gemma":[0.00002571911,0.0003945607,0.0006503953,0.00001758943,0.00005323403,0.00009331608,0.00002346083,0.03579545,0.9608886,0.0003199432,0.001692933,0.0000447899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2123867,0.003052801,0.7745264,0.0006705754,0.0003841248,0.0008799047,0.0004491842,0.005809152,0.001841178],"genre_scores_gemma":[0.327107,0.002312462,0.6643272,0.0003930548,0.0002225265,0.001196109,0.0006926171,0.000550876,0.003198164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005522727,"threshold_uncertainty_score":0.02920735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03250040043923207,"score_gpt":0.3045903687794546,"score_spread":0.2720899683402225,"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."}}