{"id":"W4401662700","doi":"10.1016/j.ijbiomac.2024.134845","title":"Serum protein albumin and chromium: Mechanistic insights into the interaction between ions, nanoparticles, and protein","year":2024,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Ministry of Colleges and Universities; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Bovine serum albumin; Chemistry; Metal ions in aqueous solution; Nanoparticle; Albumin; Chromium; Metal; Nanomedicine; Serum albumin; Biophysics; Nuclear chemistry; Biochemistry; Organic chemistry; Nanotechnology; Materials science; Biology","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":[0.0003724282,0.0001684119,0.000205584,0.0000602289,0.00007227182,0.0001992821,0.0003125907,0.0001223452,0.000150708],"category_scores_gemma":[0.0005161715,0.0000980119,0.00007504713,0.00007497511,0.0002003191,0.0001054094,0.0002225369,0.0004029567,0.000007214449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000120697,"about_ca_system_score_gemma":0.00005665363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009814681,"about_ca_topic_score_gemma":0.00000172839,"domain_scores_codex":[0.9987296,0.00008741314,0.0004856061,0.0002424609,0.0003095273,0.0001454085],"domain_scores_gemma":[0.9991879,0.0003030215,0.0001599704,0.00008313807,0.0001463761,0.0001195748],"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":[0.00006824113,0.00003255783,0.0002814198,0.0000518518,0.000228285,0.0002255031,0.0001843789,6.476398e-7,0.972145,0.003466197,0.00001533077,0.02330062],"study_design_scores_gemma":[0.0002634013,0.00009877094,0.0005671703,0.0005456906,0.00004257631,0.0003038892,0.0003408132,0.0004156747,0.9549391,0.03579123,0.006518378,0.0001733367],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990658,0.001458614,0.004328044,0.003068493,0.00009042359,0.00007862493,0.000008499483,0.00002682441,0.0002825056],"genre_scores_gemma":[0.9937789,0.0001377526,0.005546026,0.00006271142,0.0002986197,0.00001385482,0.000006548227,0.00001090325,0.0001446335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03232503,"threshold_uncertainty_score":0.3996809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714797856067765,"score_gpt":0.3041808414395373,"score_spread":0.2770328628788596,"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."}}