Validating Autoclave Cycles for Carcass Disposal in Animal Biosafety Level 2/3 Containment Laboratories
Bibliographic record
Abstract
Introduction: Animal carcasses differ in composition from other types of solid waste, and through prior testing it was determined that cycle parameters applied to general, solid biohazardous waste did not ensure proper sterilization of ferret carcasses. Objectives: The goals of this study were to develop and validate an autoclave cycle that would ensure the decontamination of infectious animal carcasses before removal from an animal biosafety level 2/3 containment suite for downstream disposal and to test different ways to prepare and package animal carcasses for autoclaving. Methods: Intact ferret carcasses were implanted with biological indicators, and the carcasses were placed in biohazard bags, then into metal pans. To test the efficacy of the autoclave cycle on larger biomasses, 1, 2, or 4 ferret carcasses were placed in a biohazard bag. A total of 4 carcasses were placed in each pan. An autoclave cycle was created to begin the study. After initial tests, minor modifications to the initial test cycle parameters were made, and a new cycle was validated for ferret carcasses up to 2 kg each. Parameters for the validated cycle were as follows: sterilization time 240 minutes, temperature 125°C, 5 prevacuum pulses, and chamber pressure 15 psi. Results: The results of this study indicate that an extended sterilization time is required to successfully decontaminate animal carcasses compared with regular, solid, and biohazardous waste. Conclusions: This study demonstrates that it is possible to sterilize multiple intact ferret carcasses per load under validated autoclave cycle conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".