Construction of a tertiary model and uncertainty analysis for the effect of time, temperature, available chlorine concentration of slightly acidic electrolyzed water on salmonella enteritidis and background total bacteria counts on chicken
Bibliographic record
Abstract
This study aimed to investigate the combined effects of storage time, temperature, and available chlorine concentration (ACC) of slightly acidic electrolyzed water (SAEW) on Salmonella Enteritidis (S. Enteritidis) and total viable background counts (TVC) on chicken meat surfaces. Models were validated with high accuracy (adj-R 2 > 0.95; RMSE < 0.20), and sensitivity analysis showed significant effects of time, temperature, and ACC on bacterial growth ( P < 0.05). Furthermore, temperature notably reduced the proportion of S. Enteritidis within TVC from 55% to 33% at lower temperatures ( P < 0.05), while ACC significantly affected maximum bacterial growth (a), growth rate (k) ( P < 0.05), and turning points in the growth curve (x c ) parameters of models. Furthermore, temperature and ACC interactions synergistically influenced growth rate (k) and turning point (x c ) parameters. Monte Carlo simulation supported the models' predictive capability in estimating S. Enteritidis distribution on chicken meat surfaces under varied conditions. The results from this study contribute to microbial risk assessments of S. Enteritidis in the chicken. • Built growth model using time, temperature, and SAEW for S. Enteritidis and TVC. • Temperature impacted S. Enteritidis more than TVC, altering its proportionality. • Found ACC, temperature, and their interaction had linear effects on parameters. • Proposed model to assess S. Enteritidis microbial risks on chicken.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".