Microbiological Properties of Cows Meat Dehydrated Using Solar-Drying, Sun-Drying and Oven Drying
Bibliographic record
Abstract
Meat samples were dipped in three different concentrations (2, 4 and 8 %) of sodium chloride combined with 120ppm sodium nitrite and 300ppm ascorbic acid for 30 minutes at room temperature (30°C). Meat samples were then separated into two equal batches and dried by two methods (solar or oven drying) of dehydration. Untreated meat samples were used as control and dried by sun-drying. Dehydrated meat samples were kept in plastic containers for two months at room temperature. Meat samples were taken after drying and during storage for microbiological (total plate count, coliforms / faecal coliforms, Staphylococci and molds and yeasts counts) analyses. Results showed that meat strips dipped in NaCl combined with preservatives decreased gradually log No/ g. The methods of drying were found to have a significant effect on decreasing microbial count and were higher in oven followed by solar and sun-drying. Both solar and oven drying were found to be better than sun-drying but due to energy cost solar-drying could be considered the best.
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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 | 0.000 |
| 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".