{"id":"W2081832172","doi":"10.1007/s12195-008-0035-5","title":"Kinetic Characterization by Surface Plasmon Resonance-Based Biosensors: Principle and Emerging Trends","year":2008,"lang":"en","type":"article","venue":"Cellular and Molecular Bioengineering","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biotechnology Research Institute; National Research Council Canada; Polytechnique Montréal","funders":"","keywords":"Surface plasmon resonance; Biosensor; Nanotechnology; Characterization (materials science); Identification (biology); Biochemical engineering; Computer science; Data science; Materials science; Engineering; Biology; Nanoparticle","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":[0.00006441771,0.0001754851,0.0002069861,0.0001175081,0.00009563084,0.00001658012,0.00003989389,0.00007419947,0.00002073044],"category_scores_gemma":[0.00001477302,0.0001627543,0.00005011737,0.0001943548,0.00008204321,0.00003489674,0.00004038816,0.0001400976,0.000002899389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001544557,"about_ca_system_score_gemma":0.00001791276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002130245,"about_ca_topic_score_gemma":2.530154e-7,"domain_scores_codex":[0.9990575,0.00001794847,0.000161855,0.0002747784,0.0002119146,0.0002759585],"domain_scores_gemma":[0.9996014,0.00001416414,0.00002555558,0.0001380103,0.00003295403,0.0001879545],"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":[0.00006083501,0.00002961918,0.003695914,0.0001208963,0.00002032634,0.0002129482,0.00006438386,0.0000873422,0.9933804,0.00005641745,0.00003925893,0.002231668],"study_design_scores_gemma":[0.0009182536,0.0001912227,0.01167134,0.0001021108,0.00002904942,0.0001226765,0.000008887925,0.04638422,0.881925,0.000001042751,0.05839685,0.0002493146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893239,0.004698085,0.005064647,0.0005332087,0.00004085807,0.0001149592,0.00002165131,0.00005209118,0.000150642],"genre_scores_gemma":[0.9965268,0.0008449779,0.0008905317,0.0001055351,0.00003569342,0.000004745954,0.0002412888,0.00003151759,0.001318924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1114554,"threshold_uncertainty_score":0.6636926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01098545566237296,"score_gpt":0.2407447682217541,"score_spread":0.2297593125593812,"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."}}