USE OF THE METHOD OF ELECTRON PARAMAGNETIC RESONANCE FOR DETERMINATION OF ABSORBED DOSES OF IONIZING RADIATION OF DIFFERENT TYPES OF MEAT AND FISH RAW MATERIALS
Bibliographic record
Abstract
To determine the absorbed doses of ionizing radiation of food, it is recommended to use the method of electron paramagnetic resonance (EPR), but, at the same time, determination method improvement is necessary. The objective of the study is improvement of the technique of sample preparation and analysis of the obtained results by means of quantitative estimation of the absorbed doses of ionizing radiation on the basis of EPR spectrum parameters, case study is irradiated meat and fish. Bone tissue samples (BTS) of meat and fish were subject to irradiation processing with ionizing radiation in the following doses: 3, 9, 10, 12 kGy with UELR-10-10C2 linear electron accelerator with energy up to 10 MeV. Study of the irradiated samples was performed with the automated portable X-band EPR spectrometer of the brand Labrador Expert. The improved technique of preparation of bone tissue samples for analysis differs with the increased duration of drying - up to 24 hours, which allows to obtain the stable EPR spectra in multiple replications. Correlation dependence of EPR signal area increase and irradiation dose is determined: for beef it is 0.98, for pork it is 0.98, for poultry it is 0.996 and for fish it is 0.99. Strong statistical relationship between the irradiation dose and the absorbed dose is determined: for beef it is 0.94, for pork it is 0.94, for poultry it is 0.96 and for fish it is 0.94. Processing of EPR spectra of meat and fish BTS by means of amplitudecalculation and EPR peak width and area allows to determine the absorbed dose with a high degree of confidence (p ≤ 0.05). For bone tissue of pork, beef, poultry and fish, irradiated with the dose of 12 kGy, amplitude is 4.8∙10-4, 5.08∙10-4, 1.11∙ 10-4 and 3.44∙10-5 p.u., peak area is - 6.73∙ 10-3, 6.94∙10-3, 3.68∙10-3 and 3.07∙10-3.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".