{"id":"W4387046383","doi":"10.1039/d3an01117h","title":"Influence of bovine and human serum albumin on the binding kinetics of biomolecular interactions","year":2023,"lang":"en","type":"article","venue":"The Analyst","topic":"Protein Interaction Studies and Fluorescence Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Regroupement Québécois sur les Matériaux de Pointe","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Bovine serum albumin; Kinetics; Human serum albumin; Chemistry; Serum albumin; Human albumin; Receptor–ligand kinetics; Plasma protein binding; Biosensor; Albumin; Chromatography; Biochemistry; Receptor","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":[0.0001719208,0.00007598446,0.0001188269,0.00008071224,0.0001128539,0.000009071874,0.0001703718,0.0000249204,0.00001321527],"category_scores_gemma":[0.00007929873,0.00004444306,0.00009117286,0.0003824017,0.0001551751,0.000002740032,0.0001415261,0.00006194978,0.000007960008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004100682,"about_ca_system_score_gemma":0.000004587731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001390059,"about_ca_topic_score_gemma":0.00008481162,"domain_scores_codex":[0.9994208,0.00005200427,0.0001958485,0.0001290023,0.0001044829,0.00009792086],"domain_scores_gemma":[0.9993818,0.00004156533,0.0001388143,0.0003335872,0.00008746891,0.00001676422],"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":[0.00001468295,0.00001842087,0.002126581,0.000006847957,0.000223095,6.729134e-7,0.00006330977,0.0002909302,0.9962261,0.0002811948,0.0006233956,0.0001247908],"study_design_scores_gemma":[0.00009344163,0.0002114976,0.01747114,0.00003904508,0.0001132979,0.000002437469,0.0006387637,0.0001336526,0.976921,0.00005523687,0.004248051,0.00007245066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998417,0.00007659322,0.0001312133,0.001040879,0.00001389917,0.00006608462,0.00001691692,0.000004055424,0.0002334045],"genre_scores_gemma":[0.9992838,0.0001646833,0.00001071172,0.0001005113,0.00003024247,0.000008664788,0.00001441144,0.000005978616,0.0003809898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01930509,"threshold_uncertainty_score":0.1812335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585862280466383,"score_gpt":0.2944431605314582,"score_spread":0.2785845377267944,"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."}}