Bibliographic record
Abstract
Different Candida species have distinct susceptibility patterns.Thus, to overcome the high mortality associated with candidemia, rapid species identification is crucial to guide antifungal therapy before susceptibility testing results are available.Blood culture (BC) still is the diagnostic gold standard for the detection of candidemia, even though its sensitivity is low, and the time to positivity often exceeds 48 hours.Recently, a method utilizing T2 magnetic resonance (T2MR) for the detection of pathogens in whole blood was developed.The aim of our study is to evaluate the T2MR system (T2 Biosystems) for the detection of candidemia in comparison with BC and the SeptiFast (Roche) -a well established molecular test.In addition, serum levels of B-D-Glucan and mannan are quantified to allow interpretation of discordant results.So far, sample sets from 51 different blood draws (31 patients with suspected candidemia) were analyzed.In thirty sets, all three tests gave negative results.An invalid T2MR result and negative SeptiFast and blood culture were noted in one case.Bacterial pathogens were detected by blood culture and/or SeptiFast in nine episodes.In two cases, Candida was detected by all tests.In six sets, blood cultures remained negative, but Candida was detected by both molecular tests.In two sets, only T2MR gave a positive result, while T2MR remained negative in one sample even though Candida was detected by SeptiFast.This preliminary dataset shows that molecular tests are valuable add-ons to BC; due to the low number samples positive for Candida, further conclusions are not yet possible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.872 | 0.708 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".