Inactivation of Vegetative and Sporulated Bacteria by Dry Gaseous Ozone
Bibliographic record
Abstract
Inactivation by gaseous ozone of different types of microorganisms is successfully achieved provided, as is well known, the gaseous phase is strongly humidified. The inactivation mechanisms and species involved in this process are, however, not yet clearly identified. To gain insight, we considered exposure of bacterial spores to dry rather than humidified ozone, a less complex chemical environment. In contrast to most of the published literature, it is shown that, under strict dry ozone conditions, bacterial spores can be inactivated, but to a degree that is largely dependent on the spore type and substrate material. In this case, the O3 molecule is determined to be responsible for the inactivation process through its diffusion into and oxidative action within the spore, as no outer erosion of the spore is detected. With humidified ozone, a higher inactivation efficiency is observed that is most probably related, in part, to the swelling of the spore, which facilitates the diffusion of oxidative species within it and up to the core; besides O3, these oxidative agents stem from the interaction of O3 with H2O, which in the end leads to a heavily damaged spore structure, in contrast to dry-ozone exposure where the spore integrity is maintained.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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".