Artificial sweeteners in Ontario streams
Bibliographic record
Abstract
To quantify the influence of septic system effluent on streams, 294 samples from 173 stream sites in southern Ontario, Canada, were collected between 2008 and 2015 and analyzed for four artificial sweeteners, acesulfame, saccharin, cyclamate, and sucralose. These artificial sweeteners are powerful tracers of wastewater in the environment due to their widespread use in consumer products and their high concentrations in raw and treated wastewater. Septic systems are known to contribute artificial sweeteners to groundwater, which can subsequently discharge to surface waters. 91% of the stream water samples collected as part of this dataset contained one or more artificial sweeteners, indicating a contribution of groundwater that originated from septic system effluent. Detailed information on the collection and interpretation of this data is published in Journal of Hydrology X 7: 100050. https://doi.org/10.1016/j.hydroa.2020.100050.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".