{"id":"W2614375104","doi":"10.1021/acsomega.7b00110","title":"Development of <i>Escherichia coli</i> Asparaginase II for Immunosensing: A Trade-Off between Receptor Density and Sensing Efficiency","year":2017,"lang":"en","type":"article","venue":"ACS Omega","topic":"Acute Lymphoblastic Leukemia research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO; Centre in Green Chemistry and Catalysis","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Surface plasmon resonance; Chemistry; Chelation; Analyte; Antibody; Reproducibility; Covalent bond; Tetramer; Detection limit; Immunoassay; Escherichia coli; Combinatorial chemistry; Chromatography; Nanotechnology; Materials science; Biochemistry; Nanoparticle; Enzyme; Immunology; Biology; Organic chemistry","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":[0.0006098293,0.0005937152,0.0003619853,0.000215111,0.0001447162,0.000577821,0.0006992502,0.0006445798,0.0009269698],"category_scores_gemma":[0.0005999477,0.0003969973,0.0002914248,0.0002065885,0.0002675032,0.0003245098,0.0003105294,0.0006192181,0.0006677283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003749014,"about_ca_system_score_gemma":0.0001837935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004476379,"about_ca_topic_score_gemma":0.0009819682,"domain_scores_codex":[0.9993924,0.0001268897,0.00004564163,0.0001938302,0.000185502,0.00005575031],"domain_scores_gemma":[0.9997024,0.00008251426,0.00007276262,0.00003418391,0.00006906057,0.00003900483],"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":[0.0000112349,0.000004560198,0.00002507705,0.00001518678,0.000001672577,0.000006653888,0.000004037866,0.00001903721,0.9993936,0.00002708121,0.00001668183,0.0004752296],"study_design_scores_gemma":[0.000001743172,0.00003444452,0.0002371704,0.000002391822,0.000002573849,0.00003828438,0.000004760604,0.0006820542,0.9983474,0.000008991742,0.0006376586,0.000002398169],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8313331,0.003068086,0.1587056,0.0006050646,0.0001545229,0.0002461298,0.0004421739,0.00103873,0.004406595],"genre_scores_gemma":[0.8219988,0.00229936,0.1678084,0.0004046413,0.00004725665,0.000286133,0.0007497077,0.0001785684,0.006227215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009269698,"threshold_uncertainty_score":0.003225148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03060168355825527,"score_gpt":0.3018551914618368,"score_spread":0.2712535079035815,"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."}}