Trace elements in Canadian field peas: a grain safety assurance perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Canada is a significant exporter of field peas and, thus, issues of food safety are important in all grain and food products within the international marketplace. Environmental contaminants, such as trace elements, may be present in all foods and, as a result, international standards have been established for a number of toxic trace elements, such as cadmium, lead, mercury and arsenic, in raw food commodities and food products. The Canadian Grain Commission has undertaken a baseline study of various trace elements in Canadian peas to ensure compliance with international food safety legislation. Mean total cadmium content was found to be 0.023 mg kg(-1); arsenic and lead mean values were below the method limit of quantification of 0.050 mg kg(-1) and the total mean mercury level was below the quantification level of 0.002 mg kg(-1). All measured values in the study were below the maximum residue levels (MRLs) established by the FAO and WHO in the Codex Alimentarius. The mean total selenium content was 0.331 mg kg(-1), with 56% of the measured values exceeding the MRL established by the People's Republic of China (PRC) of 0.3 mg kg(-1). No Codex MRL has been established for selenium as it is regarded as an essential trace element for human health and the PRC is currently reviewing its MRL for selenium in light of this fact. For those parts of the world where selenium-deficiency is of nutritional concern, the higher level of selenium in Canadian peas and their products may be of nutritional benefit.
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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 | 0.001 | 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) | 0.007 | 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 it