Evaluation of Surface Enhanced Raman Spectroscopy (SERS) for Detection of Acetone in the Context of Food Safety and Quality Application
Bibliographic record
Abstract
Development of sensors for detection of contaminated food products is important to ensure safety of the community. This paper focuses on detection of a compound, acetone associated with pathogen contamination and spoilage of beef in packaged condition. Surface Enhanced Raman Spectroscopy (SERS) technique was used to develop an integrated sensing system. This sensing system utilized laboratory prepared silver sol as the SERS substrate to detect acetone at low ppm and high ppb concentration. A set of eight experiments with two different experimental conditions were conducted. The first four set provided an estimated lower detection limit (LDL) ranging between 69.63 ppm and 630.17 ppm corresponding to the 1711 cm-1 and 532 cm-1 Raman shift (cm-1) regions, respectively. The second four sets of experiments provided a lower estimated LDL ranging between 9.78 ppm and 43.45 ppm corresponding to 1222 cm-1 and 532 cm-1, respectively. This study demonstrated the ability of this sensing system to detect the indicator compound.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".