The utilization of hydrophobic wax beads for the absorption of gas particles: A one health approach to address fuel spills in lake Muskoka
Bibliographic record
Abstract
The prevalence of recreational, motorized boating on freshwater lakes has significantly increased in the last decades. Consequently, there has been an increase in fuel spills and an accumulation of toxic polycyclic aromatic hydrocarbons (PAHs), which can have significant adverse health impacts on humans, non-human animals, and the environment. As previous initiatives to clean up spills have often been invasive, tough to follow, and environmentally intolerant, a One Health approach is necessary to address this issue. This article proposes a cost-effective and environmentally friendly solution to remove PAHs from Lake Muskoka in Ontario, Canada. The solution, based on principles of hydrophobic interactions, employs Carnauba wax beads in mesh cages to absorb PAHs from the water. This natural absorbent technology could lead to improvements in the overall quality of life and health of humans, non-human animals, and the environment. If deemed successful, this technology may be adapted to other bodies of water to mitigate the damage of PAHs on freshwater ecosystems.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".