Implications of Multiple Rinsing on Recovery of Bacteria from Fresh Produce
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Washing fruits and vegetables before eating is recommended to reduce the chance of foodborne illness. Rinsing may not be as effective in removing microorganisms, as consumers believe. The current study determined the effect of multiple water rinses in removing bacteria and yeasts/molds in the first study and compared multiple commercial solution and water rinses in the second study. In the first study, over 3 logs of aerobic bacteria per ml of rinse and almost 2 logs of yeasts/molds per ml of rinse were recovered from the fifth rinse. Grapes had very low bacteria and yeasts/molds counts (< 1.0 log CFU/ml of rinse) compared to the other five produce products (2 to > 4.0 CFU/ml of rinse) tested and the commercial rinses did not reduce the number of bacteria or yeasts/molds recovered from the produce greater than water rinsing. Based on this and other studies, consumers should be aware that produce that has been rinsed can retain high populations of microorganism on their surface.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it