TRACE ELEMENTS IN BLOOD SERUM OF SÃO PAULO YOUTHS MEASURED BY PIXE
Bibliographic record
Abstract
The level and change in concentration of trace elements in the fluids of a body may be the result and an evidence of alterations in life functions. In the search for trace element alterations in the human body it is necessary to know referenced values for as many elements as possible. In this work, Proton Induced X-ray Emission (PIXE) was used to study elemental concentrations in human blood serum of 30 healthy donors. The serum samples were obtained by centrifugation and were micro-pipetted on 10µm thick Nuclepore film for PIXE analysis. The elemental concentrations were calculated relative to an internal yttrium standard added during sample preparation. A total of 9 elements were measured (P, S, Cl, K, Ca, Fe, Cu, Zn and Br) in good agreement with literature data. The accuracy of the method was verified analysing reference serum samples from the NIPH-Québec (ICP04S-06 and ICP02S-05). A preliminary statistical analysis indicated a log-normal distribution only for Fe and Cu, while concentration data for the other elements followed the normal distributions. This result indicates the need for stronger statistical data set since the distribution of the elemental concentrations may be a criterion to access their role in biological functions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".