Chitosan – A Natural Adsorbent for Copper Ions
Bibliographic record
Abstract
As a result of industrial activities and technological changes, a high and continuously increasing amount of heavy metals and heavy metal containing effluents are released into the environment by different industrial nations.These metals cannot be degraded.Furthermore, because of their toxicity, they are highly detrimental to the environment and human health.Heavy metals accumulate in the food chain and become permanent pollutants in the environment.In the human body they accumulate in different organs causing serious damage.To overcome this problem, the adsorption behaviour of heavy metal ions, in particular copper ions was investigated by apply chitosan flakes, powder, and beads as a natural adsorbent.Metal removal was studied using adsorbance measurements, SEM-EDX, and size measurements.The adsorption capacity of chitosan was determined at different concentration and times.The received adsorption capacities for copper ions were very promising, with a maximum value of 150 mg/g on chitosan powder.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.001 |
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".