Inter-Laboratory Evaluation and Successful Implementation of MS2 Coliphage as a Surrogate to Establish Proficiency Using a BSL-3 Procedure
Bibliographic record
Abstract
The U.S. Environmental Protection Agency’s (EPA) Water Laboratory Alliance relies on the Centers for Disease Control and Prevention’s ultrafiltration-based Water Processing Procedure (WPP) for concentration of biosafety level 3 (BSL-3) agents from 10 L to 100 L of drinking water. The WPP requires comprehensive training and practice to maintain proficiency, resulting in a critical need for quality control (QC) criteria. The aim of this study was to develop criteria using male-specific (MS2) coliphage (BSL-2 agent) to minimize safety hazards associated with BSL-3 agents and to use the criteria to evaluate analytical proficiency during a demonstration exercise. EPA Method 1602 with EasyPhage was used during the study to develop QC criteria for 100-mL, and 40–100 L samples. The demonstration exercise indicated that the MS2 criteria would allow laboratories to demonstrate proficiency using the WPP with 40–100 L samples. In addition, the QC criteria developed for 100-mL samples has broad applicability at laboratories that are using MS2 for other types of analyses, such as assessment of water treatment devices. The development of MS2 QC criteria allows laboratories to develop and confirm ongoing proficiency using the WPP.
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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 | 0.043 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".