The Effects of Water Hardness on Daphnia Response to Chloride Exposure.
Bibliographic record
Abstract
Freshwater salinization is a major issue in Canada with nearly 6 million tones of road salt (typically NaCl) used annually for road de-icing. Many aquatic organisms show sensitivity to salt, leading to the creation of the Canadian Water Quality Guidelines (WQG). The WQG were created to determine chloride (Cl) levels that would protect most aquatic species from salinization. Two concentrations were created for long-term and short-term exposure, 120mg/L and 640mg/L, respectively. However, research indicates aquatic organisms in soft water (low calcium, or Ca) can experience negative effects of Cl below the WQG. The mechanisms by which Cl and Ca interact are unknown, but one proposed hypothesis suggests that Ca tightens cellular junctions reducing the passive flow of ions into aquatic organisms. Collaborating with Dr. A. Donini (York U), we measured hemolymph Ca and sodium (Na) ion concentrations in Daphnia that were cultured in FLAMES media treated with 1 to 70 Ca mg/L (CaSO4 · 2H2O) crossed with 0.39 to 400 Cl mg/L (NaCl) to identify if they showed varying concentrations of hemolymph ions. Daphnia were cultured in untreated FLAMES media and fed Scenedesmus obliquus at 2mgC/L/day for 2 generations. Neonates <24 hours old were transferred to treatment media and fed the same regimen for 6 days, then hemolymph ion concentrations were measured using ion-selective microelectrodes. The experiment is still ongoing. We predict lower hemolymph Na concentrations for a given level of Cl as Ca treatment increases. Understanding the varying effects of Cl at different Ca concentrations will be helpful in adequately reforming the WQG.
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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 | 0.000 |
| 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) | 0.001 | 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".