Odourous algal-derived alkenes: differences in stability and treatment responses in drinking water
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.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".