Metals Precipitation from Effluents: Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At the onset of 21st century, the pollution of surface and groundwater by toxic metals continues to represent a challenge for the authorities responsible for environmental protection. The uncontrolled rejection of metals in aquatic ecosystems such as Ag, As, Be, Cd, Cr, Cu, Hg, Ni, Pb, Sb, Tl and Zn, constitute a serious threat to human and animal health. Several methods of treatment of waters polluted by metals have been proposed during the last several decades. However, the technique of precipitation of metals remains the most favorable option on an industrial scale due to reasons of cost-effectiveness, performance, and simplicity. The present review presents current knowledge on various technical alternatives for precipitation of metals. The discussion relates to the individual characteristics of the metal contaminants, as well as their behavior compared to various techniques of precipitation.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it