{"id":"W2969972640","doi":"10.1016/j.csbj.2019.08.003","title":"Aluminum Phosphate Vaccine Adjuvant: Analysis of Composition and Size Using Off-Line and In-Line Tools","year":2019,"lang":"en","type":"article","venue":"Computational and Structural Biotechnology Journal","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Sanofi (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; York University; Ontario Centres of Excellence","keywords":"Process analytical technology; Materials science; Attenuated total reflection; Raman spectroscopy; Adjuvant; Particle size; Particle-size distribution; X-ray photoelectron spectroscopy; Fourier transform infrared spectroscopy; Chemistry; Optics; Chemical engineering; Immunology; Physics; Medicine","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":[0.00007159853,0.000105142,0.0002931204,0.0002309567,0.00005454428,0.00002823713,0.00003501618,0.0001400709,0.00002567835],"category_scores_gemma":[0.00001283392,0.00008756881,0.00003529044,0.0003317307,0.00006531652,0.000111176,0.00002792511,0.0002404362,2.622948e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001994911,"about_ca_system_score_gemma":0.000004909918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004375603,"about_ca_topic_score_gemma":0.00000495007,"domain_scores_codex":[0.9993912,0.00001325067,0.0002800833,0.0001242552,0.00007727858,0.0001139211],"domain_scores_gemma":[0.9997261,0.00007758458,0.00006841704,0.00003983216,0.00004550816,0.00004252987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001700693,0.00001646344,0.02657427,0.0001059519,0.0007884594,0.00002425994,0.00008918111,0.6742435,0.1565241,0.001116369,0.000005437188,0.140342],"study_design_scores_gemma":[0.0005191343,0.00005822235,0.2051671,0.00002589047,0.0001079062,0.0002245203,0.00002371014,0.787571,0.004153821,0.002055038,0.000006949896,0.00008667456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995324,0.001469124,0.002649107,0.0003894617,0.0000757618,0.00004939944,0.00001828344,0.00002143061,0.000003504317],"genre_scores_gemma":[0.9970728,0.0004190412,0.00244466,0.00002599243,0.00002045194,2.208131e-7,0.000009074979,0.00000505835,0.000002711328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1785929,"threshold_uncertainty_score":0.3570952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008559270641813239,"score_gpt":0.2280225288634449,"score_spread":0.2194632582216317,"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."}}