Assessment of alternate characterization tests for prediction of taste and odour control by granular activated carbon
Bibliographic record
Abstract
The acetoxime number test was recently identified by the American Society for Testing and Materials as a method to characterize activated carbon. This adsorption isotherm gives information about the number of high energy adsorption sites on the surface of an activated carbon. A similar test uses tetrafluoromethane for the same purpose. In contrast, the more common iodine number and Brunauer, Emmet and Teller (BET) surface area parameters are a measure of the total number of adsorption sites. 2-Methylisoborneol (MIB) is reported to require high energy sites for removal, so it was hypothesized that data from acetoxime and tetrafluoromethane isotherm tests for different activated carbons would be better correlated to MIB removal than iodine numbers or BET surface areas. MIB breakthrough was monitored in rapid small-scale column tests (RSSCTs) using four natural waters and five activated carbons. Results showed no correlation between acetoxime or tetrafluoromethane isotherms and MIB breakthrough.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".