Series 1: The Use of hsp65- and erm(41)-Targeted Amplicon Sequencing in the Diagnostic Workflow for Non-Tuberculous Mycobacteria
Bibliographic record
Abstract
Evolving technologies available to clinical laboratories and laboratory-related updates to clinical guidelines both drive the need for clinical laboratories to keep their test menu updated and in line with current technological and clinical developments. Our laboratory has developed a targeted Illumina-based amplicon next-generation sequencing (NGS) assay to interrogate the hsp65 and erm(41) genes of Mycobacterium spp. for the purposes of providing species-level ± subspecies-level identification of Mycobacterium spp. organisms in clinical samples and genotypic predictions for inducible macrolide resistance (in the case of M. abscessus complex members). The developed assay demonstrated 100% sensitivity and specificity for M. tuberculosis and M. abscessus complex cultured organisms, 98% ID overall concordance relative to the available reference identification, and a nearly 60% “rescue” rate for primary samples that could not be identified using our previous method. There was 94.6% concordance between genotypic and phenotypic results for inducible macrolide resistance. The developed assay was successfully implemented in our clinical laboratory and has been accredited for clinical use.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.010 |
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".