{"id":"W145393151","doi":"10.1007/978-1-60761-454-8_17","title":"Characterization of Polysaccharides Using Mass Spectrometry for Bacterial Serotyping","year":2009,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Steacie Institute for Molecular Sciences; National Research Council Canada; Institute for Biological Sciences","funders":"Genomic Health","keywords":"Polysaccharide; Serotype; Mass spectrometry; Microbiology; Bacterial cell structure; Typing; Fragmentation (computing); Chemistry; Characterization (materials science); Computational biology; Biology; Bacteria; Chromatography; Biochemistry; Nanotechnology; Genetics; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008429889,0.0008242881,0.0005427501,0.001896339,0.0004782446,0.0005063588,0.0004456751,0.0006135918,0.001556943],"category_scores_gemma":[0.001300197,0.0002363859,0.0003960316,0.001151921,0.0003247884,0.000643093,0.0004443965,0.0007827071,0.001520943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002046854,"about_ca_system_score_gemma":0.0004049759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005316721,"about_ca_topic_score_gemma":0.0009908075,"domain_scores_codex":[0.9995257,0.00008938079,0.00003842643,0.00005715534,0.0002381166,0.00005141545],"domain_scores_gemma":[0.999377,0.0002178638,0.0001048405,0.00006465939,0.0001795183,0.00005623387],"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":[0.00002632704,0.00001921226,0.0007466571,0.00007340193,0.000009006476,0.00006196377,0.00002376949,0.00007888595,0.9868789,0.0001777239,0.000105781,0.01179828],"study_design_scores_gemma":[0.00001189415,0.000198234,0.01074904,0.00004455726,0.00003914661,0.0006830402,0.00007371367,0.004461663,0.9723518,0.000841851,0.01052042,0.00002464544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5077602,0.01365171,0.4644353,0.0009588577,0.0003661223,0.0005998009,0.003683466,0.001332974,0.007211638],"genre_scores_gemma":[0.4507601,0.01424586,0.5248207,0.0005266949,0.0001525984,0.0004221946,0.004240356,0.0002217386,0.004609753],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001896339,"threshold_uncertainty_score":0.005208433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03339512314364863,"score_gpt":0.4009709704832046,"score_spread":0.367575847339556,"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."}}