{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006411918,0.0002113463,0.0005359952,0.00009829033,0.0008722011,0.00005454396,0.0001900042,0.000152191,0.000001528514],"category_scores_gemma":[0.0008683481,0.0001900733,0.00006618168,0.0001063188,0.0003546107,0.0001128448,0.0002817321,0.0002086171,0.000006039844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002898423,"about_ca_system_score_gemma":0.000886568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004071452,"about_ca_topic_score_gemma":0.000008889014,"domain_scores_codex":[0.9983044,0.00003260198,0.0004116169,0.0003771281,0.0004089908,0.0004653049],"domain_scores_gemma":[0.9984617,0.0002772432,0.0002412384,0.0006130618,0.0001836711,0.0002231029],"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":[0.0008786948,0.0002254834,0.006109777,0.0004556043,0.0003524621,0.00005794778,0.004317351,8.49627e-7,0.8807382,0.00008586485,0.002705126,0.1040727],"study_design_scores_gemma":[0.009594855,0.0007153574,0.1012886,0.0005373382,0.0002834039,0.00008849632,0.0003970836,0.00116247,0.8415861,0.00007058815,0.04377633,0.0004994113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952896,0.0001531236,0.001901041,0.001354712,0.0001225245,0.0007045055,0.00001252184,0.00003818504,0.0004238346],"genre_scores_gemma":[0.9553109,0.000023737,0.0440123,0.0001368432,0.0001395636,0.000005569583,0.00002455206,0.00003576001,0.0003107857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1035732,"threshold_uncertainty_score":0.7750964,"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."}}