{"id":"W2047217698","doi":"10.1111/j.1574-6968.2009.01612.x","title":"Application of an immunoaffinity-based preconcentration method for mass spectrometric analysis of the O-chain polysaccharide of<i>Aeromonas salmonicida</i>from<i>in vitro</i>- and<i>in vivo</i>-grown cells","year":2009,"lang":"en","type":"article","venue":"FEMS Microbiology Letters","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Institute for Marine Biosciences; Institute for Biological Sciences","funders":"","keywords":"Aeromonas salmonicida; Polyclonal antibodies; In vivo; Lipopolysaccharide; Polysaccharide; In vitro; Chemistry; Antiserum; Microbiology; Capillary electrophoresis; Chromatography; Biochemistry; Bacteria; Molecular biology; Biology; Antibody; Immunology","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":[0.0002170701,0.0005216947,0.0002980306,0.0002848602,0.0003100652,0.0003540905,0.0002899521,0.0004679497,0.0004379585],"category_scores_gemma":[0.0003603995,0.0002135688,0.0002259735,0.0001405924,0.0002478952,0.0001527456,0.0002731489,0.0005532725,0.0004734498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002756323,"about_ca_system_score_gemma":0.0004149343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019154,"about_ca_topic_score_gemma":0.001930903,"domain_scores_codex":[0.9997703,0.00004230815,0.00001090945,0.00005569178,0.00008300685,0.00003770976],"domain_scores_gemma":[0.9998195,0.00005057115,0.00002520149,0.00002103524,0.00005752534,0.00002627087],"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":[0.00001003272,0.000005594336,0.00005544503,0.0000130641,0.000001628697,0.000008618164,0.000004703308,0.00001134101,0.9991554,0.00001033922,0.000007643022,0.000716173],"study_design_scores_gemma":[0.000002692557,0.00007101514,0.001065353,0.000003029746,0.000008405087,0.0001363836,0.00001309349,0.0003367207,0.9976165,0.00001522859,0.0007266027,0.000004845988],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8863059,0.00409877,0.1052749,0.0004551672,0.000202732,0.0002134519,0.000256343,0.0002201972,0.00297252],"genre_scores_gemma":[0.906548,0.00247693,0.08672879,0.0004392758,0.00006078641,0.0001052995,0.0004352264,0.00003422109,0.003171448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001019154,"threshold_uncertainty_score":0.002026498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00513876761179049,"score_gpt":0.2258761976936386,"score_spread":0.2207374300818481,"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."}}