MITIGATION OF TOXIC Alexandrium tamiyavanichii USING CHITOSAN-SILICA COMPOSITE
Why this work is in the frame
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Bibliographic record
Abstract
The harmful algal bloom (HABs) phenomena affects human health, ecosystems, fishing, and tourism industries. In a single occasion, the loss due to HABs can reach thousands of Ringgit Malaysia. In this study, a chitosan-silica composite (RHA-CHi) was synthesized via sol-gel technique for the mitigation of Alexandrium tamiyavanichii, a toxic HAB species isolated from Malaysian waters. Rice husk ash silica was used as the silica precursor in the composite synthesis. The FT-IR spectroscopy suggests that the chitosan was covalently bonded with the surface silanol groups. Light microscope analysis showed that the algal cells were stuck on the surface of the composite and underwent lysis. The incorporation of chitosan decreased the surface negative charge of the silica, hence, increasing the electrostatic attraction between the cells and RHA-Chi. The removal efficiency of A. tamiyavanichii was 75% using 0.1 mg/mL of RHA-Chi in 2 hours, increasing to 85% after 24 hours. Reduced removal efficiency (16%) was observed using silica alone. The findings show that the chitosan-silica composite has high potential to be used in the mitigation of A. tamiyavanichii.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it