{"id":"W2518485865","doi":"10.1371/journal.pntd.0004988","title":"Characterizing the Syphilis-Causing Treponema pallidum ssp. pallidum Proteome Using Complementary Mass Spectrometry","year":2016,"lang":"en","type":"article","venue":"PLoS neglected tropical diseases","topic":"Syphilis Diagnosis and Treatment","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Institutes of Health; National Institute of Allergy and Infectious Diseases; Vlaamse regering; Grantová Agentura České Republiky; Fonds Wetenschappelijk Onderzoek; Centers for Disease Control and Prevention","keywords":"Proteome; Treponema; Biology; Proteomics; Mass spectrometry; Bacterial outer membrane; Orbitrap; Tandem mass spectrometry; Membrane protein; Tandem mass tag; Computational biology; Quantitative proteomics; Microbiology; Chemistry; Escherichia coli; Biochemistry; Syphilis; Chromatography; Gene; Virology","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":[0.0002922492,0.0004381462,0.0003098469,0.0009425535,0.0002547785,0.0003449513,0.0002389391,0.0004567609,0.0008747143],"category_scores_gemma":[0.0005496044,0.00009581966,0.0004406493,0.0007343888,0.0001854314,0.0002592925,0.0002940334,0.0002993288,0.0004306928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001983279,"about_ca_system_score_gemma":0.0002449203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004244678,"about_ca_topic_score_gemma":0.0004431063,"domain_scores_codex":[0.9998444,0.00001320239,0.00001380959,0.00004658345,0.00005765898,0.00002418792],"domain_scores_gemma":[0.9997329,0.00006017507,0.00007468055,0.0000186818,0.00007408865,0.00003932215],"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":[0.00007572056,0.00001713619,0.002382765,0.0001160395,0.00001566472,0.0001291835,0.00003681446,0.00005866624,0.9948565,0.00003284395,0.00003471818,0.002243949],"study_design_scores_gemma":[0.00002622225,0.0006797989,0.1443749,0.00005430868,0.0001839613,0.005605625,0.0002695125,0.006850121,0.8369988,0.0002659406,0.004661901,0.00002887557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886743,0.001572606,0.007408045,0.00005845,0.00001560044,0.00004650211,0.001428868,0.00006879255,0.0007268218],"genre_scores_gemma":[0.9618771,0.001833246,0.02967123,0.0001274189,0.0000323775,0.00008922348,0.005565507,0.0000413532,0.0007626425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009425535,"threshold_uncertainty_score":0.00292623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04758482811321344,"score_gpt":0.2850209396628351,"score_spread":0.2374361115496217,"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."}}