{"id":"W1918798300","doi":"10.21083/surg.v1i2.420","title":"Development of physicochemical methods for analysis of pandemic influenza vaccine","year":2008,"lang":"en","type":"article","venue":"SURG Journal","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Health Canada","keywords":"Radial immunodiffusion; Potency; Chromatography; High-performance liquid chromatography; Chemistry; Influenza vaccine; Pandemic influenza; Resolution (logic); Coronavirus disease 2019 (COVID-19); Virology; Virus; Biology; Antibody; Immunology; Biochemistry; In vitro; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002373367,0.001104287,0.0004101815,0.001709085,0.0003907124,0.0006334233,0.0007413006,0.0006267611,0.001785795],"category_scores_gemma":[0.002844891,0.0005854261,0.0005146582,0.0005861829,0.0005792734,0.0009643321,0.0006677798,0.001636289,0.001928965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005084092,"about_ca_system_score_gemma":0.001030755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006730372,"about_ca_topic_score_gemma":0.001435661,"domain_scores_codex":[0.9984922,0.0003659853,0.00009538569,0.0002642242,0.0007273795,0.00005477874],"domain_scores_gemma":[0.9985751,0.0003540292,0.0001763101,0.0001507914,0.0006631981,0.00008062403],"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":[0.00003761191,0.00005993709,0.0005929823,0.0002411313,0.00002130066,0.00005861479,0.00003696366,0.0004786791,0.957931,0.001515532,0.0003863013,0.03863989],"study_design_scores_gemma":[0.00001845723,0.0004184382,0.004215274,0.00006827273,0.00002844036,0.0004936965,0.00006108697,0.009036709,0.9611523,0.001250239,0.02321837,0.00003872724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04497473,0.006619951,0.9374644,0.0005177251,0.0002939507,0.0007038483,0.001028363,0.001519607,0.006877374],"genre_scores_gemma":[0.1400194,0.008387041,0.8400731,0.0005024429,0.0001221159,0.001472191,0.001464883,0.0002864463,0.007672323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002373367,"threshold_uncertainty_score":0.01255172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2544793041831264,"score_gpt":0.5104688169940845,"score_spread":0.2559895128109581,"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."}}