A Permeable Reactive Barrier for Treatment of Heavy Metals
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
Historical storage of ore concentrate containing sulfide minerals at an industrial site in British Columbia, Canada, has resulted in widespread contamination of the underlying soil and ground water. The oxidation of sulfide minerals has released significant quantities of heavy metals, including Cu, Cd, Co, Ni, and Zn, into the ground water. A pilot-scale, compost-based, sulfate-reducing permeable reactive barrier was installed in the path of the dissolved heavy-metal plume. The permeable reactive barrier uses sulfate-reducing bacteria to promote precipitation of heavy metals as insoluble metal sulfides. Monitoring over a 21-month period indicated significant removal of heavy metals within the barrier. Copper concentrations declined from a mean concentration of 3,630 pg/L in the influent to a mean concentration within the barrier of 10.5 microg/L, Cd from 15.3 microg/L to 0.2 microg/L, Co from 5.3 microg/L to 1.1 microg/L, Ni from 131 pg/L to 33.0 microg/L, and Zn from 2,410 microg/L to 136 pg/L. Within the lower half of the barrier where tidal influences were more limited and sulfate-reducing conditions were better maintained, mean treatment levels of 2.9 microg/L (Cu), 0.1 microg/L (Cd), 0.4 microg/L (Co), 2.7 microg/L (Ni), and 6.3 microg/L (Zn) were observed.
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 | 0.000 | 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) | 0.004 | 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 it