Gradient diffusion susceptibility testing for Neisseria gonorrhoeae: an accurate alternative to agar dilution in high-MIC strains?
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: is not well established, especially in strains with high MICs. AIM: . METHODS: , all tested by the agar dilution method according to CLSI methods and confirmed to be genetically distinct using molecular typing (NG-MAST), were selected. Isolates with high MICs were targeted. Gradient diffusion was performed for ceftriaxone (CRO), cefixime (CFX), azithromycin (AZT), tetracycline (TET) and fosfomycin (FOS) using two different commercial antimicrobial strips on different culture media (a non-commercial GC agar base with 1 % defined growth supplement and two commercial media). The performance of agar gradient diffusion was assessed based on accuracy, using essential and category agreements (EA and CA). RESULTS: Essential and categorical agreement were over 90 % for CRO, CFX and AZT on the two commercial agar media tested. Category disagreements were seen for CFX and AZT, mostly just very major errors. For TET, EA ranged from 80 to 96 % and CA ranged from 38 to 76 %, most of the misclassifications being minor errors. Finally, EA for FOS ranged between 80 and 98 %. CONCLUSION: Gradient diffusion is an accurate and acceptable alternative for CRO, CFX and AZT. Caution is advised when MICs are reported by gradient diffusion approach breakpoints because of the possibility of very major errors. The use of gradient diffusion is limited for TET because of the high rate of minor errors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it