{"id":"W2903001438","doi":"10.20944/preprints201808.0284.v1","title":"Identity, structure and compositional analysis of adjuvanted vaccines","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Protein purification and stability","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Sanofi (Canada)","funders":"York University; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Adjuvant; Antigen; Fourier transform infrared spectroscopy; Adsorption; Characterization (materials science); Vaccine efficacy; Materials science; Chemical engineering; Chemistry; Kinetics; Nanotechnology; Biology; Immune system; Immunology; Engineering; Physics","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":[0.0001875358,0.0002069737,0.0001277346,0.0005614943,0.0001169683,0.0002320167,0.0001424703,0.0002455364,0.0008319633],"category_scores_gemma":[0.0003168402,0.0001021684,0.0001775556,0.0002507786,0.0001637032,0.00025659,0.0001662211,0.0002431387,0.0003328111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001616043,"about_ca_system_score_gemma":0.00013631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002892464,"about_ca_topic_score_gemma":0.00028622,"domain_scores_codex":[0.9998422,0.00001525629,0.00001068875,0.00003534679,0.00007539937,0.00002104854],"domain_scores_gemma":[0.9998364,0.0000260043,0.00005248106,0.00001065624,0.00005939033,0.00001507947],"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":[0.00004018193,0.000007732319,0.0008978288,0.00003346709,0.000002863729,0.00001447183,0.00001505109,0.00009641422,0.9972115,0.00003812964,0.00001366011,0.001628754],"study_design_scores_gemma":[0.00000192187,0.0001080901,0.007242197,0.000006329112,0.00001108768,0.0001006752,0.00002990934,0.001515074,0.9899927,0.00004718567,0.0009411123,0.000003717331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889467,0.0008660964,0.008427103,0.00002072041,0.00001386508,0.00002106159,0.0005943341,0.00007628704,0.001033836],"genre_scores_gemma":[0.9843712,0.0006490279,0.01209558,0.00004294996,0.000009238403,0.00004381061,0.001101159,0.0000542692,0.001632587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008319633,"threshold_uncertainty_score":0.002783179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04899624262407873,"score_gpt":0.3500285073018101,"score_spread":0.3010322646777314,"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."}}