Meat Spoilage Sensing Devices
Bibliographic record
Abstract
The safety, sustainability, and profitability of the food industry will remain a key societal challenge in the decades ahead. When meat begins to degrade, the protein decomposes and releases biogenic amines. Early detection of these volatile amines therefore provides a means to sense the onset of meat spoilage. In this work, Pd-decorated ZnO nanomaterials deposited on interdigitated electrode substrates are found to show an excellent chemiresistive response to methyl amine in air with concentrations as low as 25 ppm and with operating temperatures as low as 150 °C. These results suggest that a similar chemiresistive response to biogenic amines may be possible. Surface enhanced Raman scattering is shown to be an excellent tool for sensing biogenic amines, largely due to the chemical interactions between the amine group and the Au/Ag nanoparticles, as well as the effect of the diamine on the aggregation of the nanoparticles.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".