Mobility of essential macro- and micro-elements in interaction between artificial sweat and potential peloids of some saline lakes in Mongolia
Bibliographic record
Abstract
Abstract Individuals may experience health issues attributable to environmental pollution, sedentary lifestyles, and unhealthy dietary habits. In response, numerous non-pharmaceutical treatments and techniques have emerged, with therapy mud being one such approach. The primary aim of this research was to analyze the chemical and mineralogical compositions of peloids obtained from six salt lakes: Taigan (LI), Duruu (LII), Khadaasan (LIII), Ikhes (LIV), Tonkhil (LV), and Khulmaa (LVI) in the Gobi-Altai province of Mongolia. Sample analyses involved X-ray diffraction for mineralogical assessment and inductively coupled plasma-mass spectrometry (Agilent Technologies 7800 series in Canada) for determining the chemical composition of the solid phase. Among essential macro- and microelements, Mg, Cа, Na, K, Sr, Ga, Mo, and Se had been leached from peloid to artificial sweat. Sn (0.01 μg g –1 ) at LIV and LVI lakes and Cu (0.01 μg g –1 ) at LV lake transferred from peloids to sweat, but no mobility of these elements in other peloids was detected. Li (0.02–0.04 μg g –1 ) was adsorbed from the sweat to potential peloids in LV, LIV, LIII, and LI lakes, while As (0.04–0.09 μg g –1 ) leached from peloids to sweat in all lakes except for LII. Zn (0.01 μg g –1 ) and Cr (0.04 μg g –1 ) transferred from the sweat to peloids in all lakes. Macroelements (Na, K, Ca, and Mg) and microelements (Mo, Se), which are essential for the human body, leached from the peloid to sweat. However, the mobility of toxic elements was minimal. Among micro-elements, the transition of Sr occurred the most, which can be explained by the Sr content in the peloid.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".