{"id":"W2120081470","doi":"10.1071/ma13057","title":"Nanoparticle sample preparation and mass spectrometry for rapid diagnosis of microbial infections","year":2013,"lang":"en","type":"article","venue":"Microbiology Australia","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"","keywords":"Mass spectrometry; Complex matrix; Biomarker; Sample preparation; Biomarker discovery; Ex vivo; Bacteria; Computational biology; Proteomics; In vivo; Pathogen; Chemistry; Nanotechnology; In vitro; Chromatography; Microbiology; Biology; Materials science; Biotechnology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001253651,0.00008414947,0.0001132805,0.00003590292,0.00006562669,0.00002143366,0.00006193616,0.0001308819,0.0002802693],"category_scores_gemma":[0.0002173802,0.00008570473,0.00005113864,0.00005727995,0.0001123985,0.00000745819,0.00002822087,0.00003422657,0.00001415313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008041349,"about_ca_system_score_gemma":0.00001428997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001273018,"about_ca_topic_score_gemma":0.00006366021,"domain_scores_codex":[0.9993246,0.00005390709,0.0002189228,0.0002369158,0.00001063531,0.0001550351],"domain_scores_gemma":[0.9995717,0.00004774209,0.00008489471,0.0001638026,0.00009753557,0.00003427466],"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":[0.00001879201,0.00005672176,0.05225101,0.00001823987,0.00002536737,1.862284e-8,0.00002356545,0.000002715622,0.9435992,0.00003441287,0.00386969,0.0001002397],"study_design_scores_gemma":[0.0003361513,0.0003355446,0.01665349,0.000004179886,0.00001718316,0.00000743041,0.00001975654,0.0000102961,0.9769979,0.0001568369,0.005366102,0.00009514647],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978908,0.00004109918,0.001225444,0.0001500642,0.0001671439,0.0003804115,0.0001271101,0.0000101953,0.000007707988],"genre_scores_gemma":[0.9933221,0.00001668887,0.005818007,0.0000400276,0.00007344342,0.000100986,0.0003388624,0.000006907581,0.0002829391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03559753,"threshold_uncertainty_score":0.3494937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02394813439733793,"score_gpt":0.2851393465974676,"score_spread":0.2611912122001297,"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."}}