leaves of averrhoabilimbi as a superior low cost adsorbent for lead ii removal
Bibliographic record
Abstract
1. Abstract Bilimbi leaves (BL) as a low-cost adsorbent were effectively used to remove leadPb(II) from aqueous solution in a batch adsorption experiment. The effects of multiple parameters such as pH, ionic strength and contact time were also thoroughly investigated and optimal experimental conditions were ascertained. Based on the isotherm studies on the adsorption of Pb(II) onto BL, the maximum adsorption capacity was found to be1597.63 mg/g. Kinetic studies implicated that the adsorption data were best designated by the pseudo second order and the adsorption process of Pb(II) was concluded to be exothermic and it occurred spontaneously from thermodynamic study. While, regeneration studyshowed that base treatment was able to regenerate and improve the adsorption capability of BL. Based on the overall data obtained in this study, BL proves to be a potential low-cost material and could be employed as low-cost alternatives in wastewater treatment for the removal ofPb(II). 2. Keywords: Adsorption;Bilimbi leaves;Heavy metals; Lead; Regeneration
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How this classification was reachedexpand
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".