{"id":"W2884647841","doi":"10.7939/r3474733q","title":"Development of mass spectrometry for bacteria identification","year":2001,"lang":"en","type":"article","venue":"Library and Archives Canada (Government of Canada)","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mass spectrometry; Identification (biology); Bacteria; Chemistry; Computer science; Computational biology; Chromatography; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001879562,0.00007646585,0.0001020696,0.00001211294,0.00007257407,0.0000111395,0.0001115213,0.00002010273,0.00001749755],"category_scores_gemma":[0.000009763718,0.00008098142,0.00001780831,0.00003843582,0.00002645534,0.00001266971,0.0000405855,0.00002141932,1.154424e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002510162,"about_ca_system_score_gemma":0.0005470825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007990251,"about_ca_topic_score_gemma":0.00371479,"domain_scores_codex":[0.9991406,0.00001824473,0.0002808162,0.0001688602,0.000274253,0.0001172331],"domain_scores_gemma":[0.9996089,0.00002675219,0.0001452945,0.0001485672,0.000001375268,0.00006914381],"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":[0.0001569135,0.00001375747,0.007573434,0.00005912505,0.00002364625,4.384422e-7,0.00001911784,0.000002020855,0.9870328,0.001760156,0.00008027766,0.003278341],"study_design_scores_gemma":[0.0001615111,0.00002263623,0.1077175,0.00001310762,0.000005393359,0.000001303449,0.0004005889,0.00009256545,0.8736234,0.0001238631,0.01775209,0.00008600759],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897279,0.00004430916,0.003420775,0.000353049,0.0001324093,0.0001375702,0.00006560215,0.000002659074,0.006115764],"genre_scores_gemma":[0.979087,0.00002774271,0.01760586,0.00008944187,0.00004233815,0.000007604543,0.00006061252,0.000008592978,0.00307079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1134093,"threshold_uncertainty_score":0.3302327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006269316252125411,"score_gpt":0.1736186305471136,"score_spread":0.1673493142949882,"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."}}