Odourous algal-derived alkenes: differences in stability and treatment responses in drinking water
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
Drinking water supplies are often impacted by taste and odour (T/O) episodes caused by algal volatile organic compounds (AVOCs) from algal blooms. Treatment and control of these events is important to utility operators, as customer confidence in the safety of public drinking water supplies is based primarily on their palatability and odour. To manage T/O outbreaks successfully, knowledge about treatment responses of AVOCs and anticipation of their outbreaks are thus of major importance to the water industry. The Glenmore Reservoir and water treatment plant (GWTP) supplies drinking water to over 50% of the ca. 1 million consumers in Calgary (Alberta). Despite low nutrients and high raw water quality, the reservoir experiences periodic outbreaks of fishy/floral T/O, caused by chrysophytes and diatoms (Uroglena americana, Dinobryon spp., Synura petersenii, Asterionella formosa). These odours are produced by the unsaturated C7-C10 alkenes 2,4-heptadienal, 2,4,7-octatriene, 2,4-decadienal and 2,4,7-decatrienal, generated during from the enzymatic breakdown of algal polyunsaturated fatty acids (PUFAs). The formation, persistence and stability of these compounds in both the raw water and treatment plant is not well understood.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it