Computer controlled chamber measurements for clay adherence relevant for potential dioxin exposure through skin
Bibliographic record
Abstract
A computer-controlled mechanical chamber was used to control the contact between aluminum sheet samples laden with clay, and cotton sheet samples for the measurement of mass transfer. The contact parameters of pressure (20 to 60 kPa) and time (10 to 70 sec) were varied for 160 multiple experiments of mass soil transfer. Before log transformation the average transfer for 'First Transfer' of clay particles was 34.4 ± 6.3 mg/8.97 cm(2) while that for 'Total Transfer' was 36.1 ± 6.8 mg/8.97 cm(2). Second contact, therefore, resulted in an average transfer of 1.70 ± 0.76 mg/8.97 cm(2). These values are well above adherence values measured for potting soil and sand as reported for previous experiments using the same methodologies. Based on the univariate analysis and the multiple regression analysis we were able to see some effect of parameters on the clay adherence values. The effect of pressure increases was significant for the higher levels of 50 and 60 kPa. In addition, we observed that increases in temperature were significant for 'First Transfer,' and less so for 'Total Transfer'. Past experiments using potting soil and play sand show high adherence values to human cadaver skin over cotton sample; the same scenario would be expected for clay. This data set can be used to improve estimates of dermal exposure to dioxins found in ball clays often used by artisans in the making of pottery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".