Bibliographic record
Abstract
Some of the major industries of the Zebo region (China) include the petrochemical, pharmaceutical, china and ceramics sectors. Zibo is also abundant in natural resources. In support of the ceramics industry, they have large reserves of clay, limestone and bauxite. Consequently, there are a number of mines in the region and the outflow of acidic water from these metal and coal mines, known as acid mine drainage (AMD), is considerable. The AMD is rich in sulphate ions and contains other pollutants that are subsequently transferred to the soils and surrounding surface rivers through both irrigation and infiltration of the ground water. To understand the behaviour of the soil in the presence of infiltrating pollutants and atmospheric precipitation, soil-column experiments were performed. A chosen soil sample was undisturbed in the sense that the structure of the soil layers and any pollutants within the column were preserved when the soil was transferred to the experimental apparatus. To simulate the processes that occur within the environment (infiltration and precipitation), polluted water (liquor) from a nearby source was introduced at the top of the column and once this material has infiltrated the column, clean water was allowed to flush through the apparatus. The initial concentration of various ions in the liquor were measured and throughout the experiment, the fluid that reaches the bottom of the column was collected and analysed. The goal for the workshop is to derive a mathematical model that predicts the observed experimental time dependence of the ionic concentrations emerging from the bottom of the the apparatus. Developing the model will require an understanding of the physical and chemical mechanisms of the solute transport though the soil. This is an important first step in the eventual development of remediation schemes for the contaminated soil.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".