Factorial Design Analysis of Zn(II) Ions Adsorption on Thermally Treated Rice Husk
Bibliographic record
Abstract
<p class="zhengwen"><span lang="EN-GB">Adsorption of Zn(II) ions from aqueous solutions by thermally treated rice husk was investigated using factorial experimental design to study effects of heating temperature and period of rice husk, pH, initial Zn(II) ion concentration, adsorption temperature and contact time, and adsorbent dosage. Main and interaction effects of these factors were analyzed using statistical techniques and the results were analyzed statistically using the Student’s t-analysis and analysis of variance which were used to determine significant factors that affect the percentage removal of Zn(II). These significant factors were heating temperature of rice husk, pH, initial metal concentration, contact time, and adsorbent dosage. The interaction between two different effects also affects the percentage removal of Zn(II) ions. These include the interactions between heating temperature of rice husk and initial metal concentration, pH and initial metal concentration, and pH and the adsorbent dosage.</span></p>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".