Evaluation of decontamination strategies for cyclophosphamide
Bibliographic record
Abstract
PURPOSE: The main objective was to determine the efficacy of various types of cleaning equipment and products after deliberate contamination with cyclophosphamide. The secondary objective was to test various cleaning scenarios using these equipment and products. METHODS: The study had two phases: testing of cleaning equipment (wipe : woven microfibers - Hygen®, two layers of non-woven microfibres and an inner layer of highly absorbent viscose fibres - MicronSolo®, two layers of non-woven microfibres and an inner layer of highly absorbent viscose fibres - MicroMix®, simili-tissu (low filament production) - Tork® and, mop : woven microfibers - Hygen®, microfibre and viscose - MicroOne®) and products (disinfectant : quaternary ammonium - DR100®, chlorine 0.1% - Zochlor® - Brutab® - PCS® NPH, sodium hypochlorite 2%, cleaner : detergent - Nu- Action 3®, cleaner and disinfectant: sodium hypochlorite 0.6% + detergent - Aliflex® and water) in phase 1 and testing of various cleaning procedures in phase 2. Specific areas of a room with a laminar flow hood (class II/type B2) were contaminated with 10 mcg of cyclophosphamide. Different types of surfaces were cleaned with various scenarios and the remaining cyclophosphamide was measured by the Institut national de santé publique du Québec. All tests were performed in triplicate. RESULTS: A total of 189 samples were obtained: 42 negative controls and positive controls, 54 during phase 1 and 93 during phase 2. All products were more than 96.5% effective. The 0.1% chlorines were the most effective products. Cleaning procedures with two or three products had average cleaning efficacies of 99.94-99.99%. Efficacy increased with the number of successive cleanings. When two products were used, the average cleaning efficacy varied between 99.78% and 99.98%, depending on the surface. CONCLUSION: All cleaning products tested reduced cyclophosphamide contamination by more than 96.58%. Cleaning efficacy increased with successive cleaning. No scenario was effective in removing 100% of traces. Additional studies with larger samples should be conducted to confirm these results.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".