{"id":"W2007530541","doi":"10.1039/c3fo60712g","title":"Evaluation of the biointeraction of colorant flavazin with human serum albumin: insights from multiple spectroscopic studies, in silico docking and molecular dynamics simulation","year":2014,"lang":"en","type":"article","venue":"Food & Function","topic":"Protein Interaction Studies and Fluorescence Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Natural Science Foundation of China","keywords":"In silico; Chemistry; Docking (animal); Human serum albumin; Molecular dynamics; Computational biology; Serum albumin; Environmental chemistry; Biophysics; Biochemistry; Computational chemistry; Biology; Gene; Medicine","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":[0.0002299147,0.0001018122,0.0001628452,0.00006345064,0.00007493904,0.00000729713,0.00004787551,0.00006003985,0.000003698924],"category_scores_gemma":[0.000164117,0.00007491112,0.00004859174,0.0001472488,0.00006750986,0.00001433263,0.00005011824,0.00006678698,3.644273e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007877325,"about_ca_system_score_gemma":0.00002395854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001909037,"about_ca_topic_score_gemma":0.003750189,"domain_scores_codex":[0.9990335,0.0001731323,0.0002451162,0.0002238955,0.0002480937,0.00007626619],"domain_scores_gemma":[0.9991701,0.00003237049,0.000246138,0.000205213,0.0003335151,0.00001270193],"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":[0.0006558604,0.00008331177,0.05131248,0.00003107248,0.0004558702,8.055215e-8,0.0002842861,0.02696175,0.9176202,0.00006154996,0.000003326181,0.002530158],"study_design_scores_gemma":[0.002249378,0.005350914,0.2027553,0.00024742,0.0006048206,8.576324e-7,0.001675714,0.2417926,0.5442861,0.0006792392,0.0001447947,0.0002127801],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939492,0.0005563759,0.005006198,0.00003318128,0.0001333714,0.000260686,0.000005393367,0.000003349753,0.00005228202],"genre_scores_gemma":[0.9997739,0.00002687656,0.00005319382,0.00002292169,0.00004700976,0.00002187572,0.00004305149,0.000007807096,0.000003402022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3733341,"threshold_uncertainty_score":0.3054787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427536224529818,"score_gpt":0.2972855752479373,"score_spread":0.2730102130026391,"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."}}