Batch studies of lead adsorption from a multi-component aqueous solution onto Atlantic cod fish scale (<i>Gadus morhua</i>) substrate
Bibliographic record
Abstract
Aqueous streams often posses several contaminants that are of environmental concerns. Removing these contaminants from the multi-component phases is a challenging task. In this study, the multi-component (combination of lead and arsenic ions) batch adsorption results are analyzed with respect to initial concentrations of the contaminants (lead: 2.5, 10, and 40 mg/L; arsenic: 350 and 1000 μg/L) and pH variations (pH value of 4, 7, 9, and 11) of the bulk phase. The adsorbent selected for this research is Atlantic cod (Gadus morhua) fish scale. A general trend of reduced lead adsorptivity with increasing arsenic concentration is observed at the lower concentration of 2.5 mg/L of the heavy metal cation. The decrease in lead to arsenic concentration ratio in the bulk phase is correlated with an increase in "electrostatic attractions" or with "ion pair bridging" by the arsenic species on lead ions. However, at higher lead ion concentrations of 10 ppm and 40 ppm, the effect of arsenic on lead adsorption is insignificant.Key words: adsorption, arsenic, Atlantic cod fish scale, bio-sorption, lead, concentration ratio.
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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) | 0.001 | 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".