Spectrometric determination of silicon in food and biological samples: an interlaboratory trial
Bibliographic record
Abstract
Accuracy and precision of silicon determination in biological matrices (serum, urine, water, beer and spinach) by spectrometric techniques (when necessary after acid destruction) were assessed by means of a collaborative interlaboratory trial. The trial was set up in accordance with ISO 5725-2 (1994). The relative overall repeatability standard deviation was acceptable. It varied between 4% for spinach powder (mean content: 176 mg kg−1) and 11% for serum (mean content: 5.33 mg L−1). On the other hand, the relative overall between-laboratory standard deviation was found to vary from a satisfactorily 15% for spinach after destruction (mean content: 3.32 mg L−1) to an unacceptable 107% for spinach powder (mean content: 176 mg kg−1). The overall conclusion of the trial was that silicon determination in biological matrices can properly be performed by spectrometric techniques. However, when sample pretreatment (i.e., acid destruction) is needed prior to silicon determination problems still remain.
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 | 0.054 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".