{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002230254,0.0002924542,0.0003914747,0.0001831597,0.0002645416,0.0001665228,0.0002240292,0.0001805269,0.00004387352],"category_scores_gemma":[0.0002296654,0.0002583141,0.0001488559,0.0001841038,0.00008165994,0.000008634048,0.001404163,0.0002714813,0.0000563792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000400693,"about_ca_system_score_gemma":0.00006256303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009315524,"about_ca_topic_score_gemma":0.001207076,"domain_scores_codex":[0.99828,0.00005078553,0.0004318563,0.0007366189,0.0001906288,0.0003101103],"domain_scores_gemma":[0.9989471,0.00004419479,0.0001637776,0.0005134772,0.000149459,0.0001820268],"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":[0.00009325845,0.0001422801,0.03955654,0.0003686945,0.002002701,0.00001981731,0.0004910324,0.000368714,0.9124689,0.00003960004,0.02579287,0.01865562],"study_design_scores_gemma":[0.0009744174,0.0006784751,0.1199262,0.001687318,0.0008656661,0.00002560104,0.004227703,0.0006441135,0.6958001,0.0003846971,0.172815,0.001970737],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711708,0.0005880677,0.01778374,0.008508138,0.0005497277,0.000785115,0.00007983268,0.0000888428,0.0004456818],"genre_scores_gemma":[0.9904477,0.0003501035,0.003649045,0.0002829313,0.0007671416,0.0003354244,0.0001532841,0.00004288476,0.003971459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2166687,"threshold_uncertainty_score":0.9999869,"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."}}