Bibliographic record
Abstract
Aquatic taste and odor (T/O) is rarely produced by toxic contaminants or pathogens; nevertheless, it has major negative impacts on the public and the drinking-water industry. Consumers use T/O as a primary measure of drinking water safety, yet this criterion is poorly understood, and its origins and triggers often go untraced. Much surface-water T/O is produced by the increased production of volatile organic compounds (VOCs) by algae. These chemicals can be symptomatic of short-term problems with source, treatment, or distribution systems. At a broader level, they can signify fundamental changes in aquatic ecosystems induced by human activity. T/O varies in chemistry, intensity, and production patterns among different algal taxa, and is often linked with excessive algal growth and/or the invasion of noxious species. Some VOCs may signal the presence of potentially toxic algae and/or other associated water quality issues. Traditionally, T/O has been linked with the widespread eutrophication of many surface waters; however, there has been a recent growth in the number of T/O events reported in oligo-mesotrophic systems, for example, the Glenmore Reservoir (Calgary AB) and the Laurentian Great Lakes. From a management and public perspective, therefore, it is vitally important to monitor T/O, and to continue to work toward a better understanding of the proximal and the ultimate causes-which VOCs and algae species are involved. In the short term, odor events could be anticipated and water treatment optimized. In the long term, this approach would contribute toward more a robust management of this resource through remedial or preventative measures.
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 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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".