Phytoremediation of vanadium and nickel from wastewater using Acorus calamus
Bibliographic record
Abstract
Acorus calamus is an important medicinal plant in many cultures around the world. This plant’s recorded history reaches as far back as 287 BCE, where its main uses were water purification and as a medicinal “cure-all”. In part one, I examined the history of A. calamus, its applications in the modern world and propagation methods. The two main propagation methods I tested were via rhizomes and seeds. Rhizome growth trials were more successful in overall plant yield than the seeds. Rhizomes planted in peat had 57% plant yield, while the no-peat treatment had 40% plant yield. Part two of the study examined A. calamus ability and efficiency in extracting vanadium and nickel from experimentally treated waters. Vanadium and nickel were chosen for their importance in the environment and their enrichment in bitumen, specifically tailings ponds. Nickel is an important nutrient for plant survival and vanadium is not. Acorus calamus plants were grown in a hydroponic system with 188 plants grown inside a clean air growth chamber for three months. Every day the plants were treated with nickel-enriched solutions at three concentrations (0.0, 0.01, 0.10 mg/L) and vanadium (0.0, 0.025, 0.25 mg/L). At the end of three months, plant tissues were harvested and analyzed for metal concentrations. The results showed A. calamus extracted both vanadium and nickel from the contaminated waters with maximum values of 0.6 mg/kg and 16.3 mg/kg, respectively. Results indicate A. calamus would be an excellent candidate for phytoremediation at contamination levels well above what is found naturally occurring in Alberta’s water sources.
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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 | 0.000 | 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) | 0.000 | 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 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".