{"id":"W2167166714","doi":"10.1128/jcm.00651-11","title":"Rapid Identification of Cryptococcus neoformans and Cryptococcus gattii by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry","year":2011,"lang":"en","type":"article","venue":"Journal of Clinical Microbiology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Hospital for Sick Children; BC Centre for Disease Control; University of Toronto; Toronto Public Health","funders":"","keywords":"Cryptococcus neoformans; Cryptococcus gattii; Mass spectrometry; Cryptococcus; Matrix-assisted laser desorption/ionization; Microbiology; Cryptococcosis; Biology; Subspecies; Desorption; Chemistry; Chromatography","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":[0.001535489,0.0001326119,0.0004718153,0.0001188448,0.00004150097,0.00001300316,0.0002339618,0.0003369828,0.0002738694],"category_scores_gemma":[0.0008813965,0.0001159552,0.0002066358,0.0001572138,0.0002803229,0.00001988866,0.00005792363,0.0001671922,0.0000122161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001162755,"about_ca_system_score_gemma":0.00008662532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003641807,"about_ca_topic_score_gemma":0.000002367745,"domain_scores_codex":[0.9971387,0.000362094,0.002045146,0.000239525,0.00005782564,0.0001566511],"domain_scores_gemma":[0.9970148,0.0001086139,0.001939027,0.0002701842,0.0005778058,0.00008957169],"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":[0.0003737498,0.0002665327,0.01314053,0.00003800084,0.0001038144,5.668315e-7,0.00004439348,9.789356e-7,0.9832745,0.00003081589,0.001164775,0.001561304],"study_design_scores_gemma":[0.001464727,0.001071943,0.1052923,0.00003814196,0.0001072378,0.00007065579,0.00006212274,0.00002393031,0.8888767,0.0002054242,0.002628562,0.000158322],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927641,0.0003143386,0.00612738,0.00007873517,0.0003944461,0.0001953829,0.00006028257,0.000004985853,0.00006039219],"genre_scores_gemma":[0.993858,0.0003471743,0.005250299,0.00005236332,0.0001505242,0.000002489372,0.00012788,0.00001370749,0.0001975693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09439787,"threshold_uncertainty_score":0.4728515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0294021617546783,"score_gpt":0.3057768132317325,"score_spread":0.2763746514770542,"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."}}