Wild-type cutoff values for standard broth microdilution antimicrobial susceptibility testing of Yersinia ruckeri isolates
Bibliographic record
Abstract
Yersinia ruckeri is a Gram-negative bacterium that causes enteric redmouth disease. It commonly infects farmed salmonid fishes, often requiring antimicrobial treatment. Studies on antimicrobial susceptibility patterns of Y. ruckeri have found isolates with decreased susceptibility but have lacked internationally harmonized criteria, known as epidemiological cutoff values (ECVs), which provide consensus on identifying antimicrobial resistance. To address this need, we gathered minimal inhibitory concentration (MIC) testing data for 9 antimicrobials, generated at 22°C for 24-28 and/or 44-48 h using the standard broth microdilution testing method published by the Clinical and Laboratory Standards Institute (CLSI). The dataset includes MIC data from up to 431 isolates from 7 independent laboratories. Data for each antimicrobial were analyzed with the programs Normalized Resistance Interpretation (NRI) and ECOFFinder to compare the means and standard deviations for the 2 timepoints, and to calculate wild-type cutoff values. The parameters for the timepoints were very similar, which confirmed cutoffs were only needed for the 24-28 h incubation. The cutoff values for 8 of the 9 antimicrobials are potential ECVs that have been proposed to CLSI's Subcommittee on Veterinary Antimicrobial Susceptibility Testing. Calculated cutoffs for the final antimicrobial, erythromycin, were off-scale because the MIC values clustered at higher drug concentrations. The resulting new ECVs will be included in the next edition of the VET04 supplement, which will help clinicians and researchers advance antimicrobial resistance surveillance of this bacterium.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".