Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perfluoroalkyl acids (PFAAs) are ubiquitous in nature and pose serious health risks to humans and animals. Limiting PFAA exposure requires novel technology for their effective removal from water. We investigated the efficacy of biosolid-based activated carbon (Bio-SBAC) in removing frequently detected PFAAs and their precursor fluorotelomer compounds at environmentally relevant concentrations (∼50 μg/L). Batch experiments were performed to investigate adsorption kinetics, isotherms, and leachability. Bio-SBAC achieved >95% removal of fluorotelomeric compounds, indicating that the need for PFAA removal from the environment could be minimised if the precursors were targeted. Kinetic data modelling suggested that chemisorption is the dominant PFAA adsorption mechanism. As evidenced by the isotherm modelling results, Freundlich adsorption intensity, n<sup>-1</sup>, values of <1 (0.707-0.938) indicate chemisorption. Bio-SBAC showed maximum capacities for the adsorption of perfluorooctanoic acid (1429 μg/g) and perfluorononanoic acid (1111 μg/g). Batch desorption tests with 100 mg/L humic acid and 10 g/L NaCl showed that Bio-SBAC effectively retained the adsorbed PFAA with little or no leaching, except perfluorobutanoic acid. Overall, this study revealed that Bio-SBAC is a value-added material with promising characteristics for PFAA adsorption and no leachability. Additionally, it can be incorporated into biofilters to remove PFAAs from stormwater, presenting a sustainable approach to minimise biosolid disposal and improve the quality of wastewater before discharge into receiving waters.
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.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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