{"id":"W4378802867","doi":"10.32920/23271857","title":"First Steps To Nanomedicine: Assessing Interactions Between Polystyrene Nanoparticles And Albumin Proteins","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Protein Interaction Studies and Fluorescence Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Calgary","funders":"University of Calgary","keywords":"Bovine serum albumin; Nanomedicine; Biophysics; Nanoparticle; Chemistry; Fluorescence; Serum albumin; Albumin; Fluorescence spectroscopy; Polystyrene; In vivo; Fluorescence correlation spectroscopy; Kinetics; Nanotechnology; Chromatography; Biochemistry; Materials science; Polymer; Biology; Organic chemistry; Physics; Biotechnology; Molecule","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":[0.0006677525,0.0006573463,0.0004987961,0.0004399327,0.0004708746,0.001026345,0.0004768698,0.001048583,0.002733467],"category_scores_gemma":[0.001077103,0.0004155516,0.0003497691,0.0002386361,0.0005114224,0.0009657108,0.0005734731,0.001361991,0.001247961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008134751,"about_ca_system_score_gemma":0.000974468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00202181,"about_ca_topic_score_gemma":0.002065346,"domain_scores_codex":[0.999626,0.00006398136,0.0000133693,0.00004901908,0.0001952499,0.00005245841],"domain_scores_gemma":[0.9996176,0.0001467558,0.00004393011,0.00003596893,0.0001041703,0.00005153899],"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":[0.00009298121,0.00005695999,0.0006248309,0.0001402395,0.00001181632,0.0001053887,0.00007950504,0.0004753429,0.9859335,0.0007608969,0.0005566423,0.01116182],"study_design_scores_gemma":[0.000008298489,0.0002770191,0.002618103,0.00001726179,0.00001160593,0.0002466085,0.00007846612,0.008361471,0.9823592,0.001449923,0.004554919,0.00001710235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6134496,0.007944711,0.3479391,0.003979158,0.0003970866,0.001031085,0.001051085,0.002544885,0.0216633],"genre_scores_gemma":[0.7985328,0.004227738,0.1776636,0.001368256,0.0001033559,0.0004599754,0.000819364,0.0003616088,0.01646324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002733467,"threshold_uncertainty_score":0.009144366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0414573648139852,"score_gpt":0.335731207036059,"score_spread":0.2942738422220738,"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."}}