Investigating the use of chlorine stable isotopes to identify sources of chloride in stream water
Bibliographic record
Abstract
Chloride is often assumed to be a conservative ion in the hydrological cycle and is used as a tracer ion to represent marine input via atmospheric deposition to inland fresh waters. Consistently observed discrepancies between measured catchment deposition chloride input and stream water exports are often resolved by inferring that the excess chloride enters watershed systems as unmeasured fog and/or dry deposition. The application of chloride as a marine tracer has been verified to some extent in watersheds close to the ocean where sea spray is easily measured. However, chloride deposition as aerosols or fog has not been measured and quantified for watersheds further inland. Chlorine stable isotopes offer a new method to distinguish sources of chloride in stream water. Values of chlorine stable isotopes are reported as δ37Cl, a ratio of 37Cl / 35Cl in reference to Standard Mean Ocean Chloride. Analytical uncertainty resulting from daily repeat analyses of seawater is better than 0.26‰ (1σ) and represents uncertainty from sample preparation and instrument precision. In southwestern Nova Scotia, the chlorine stable isotope composition of fog (-1.71‰ to -0.21‰), precipitation (-2‰ to -1‰), soil solution of B and C horizons (-1.57‰ to -0.81‰), mineral-bound chloride of soil and bedrock (-0.96‰ to +2.3‰), and stream water of two watersheds (-1.5‰ to -0.5‰) confirms that precipitation is not the sole contributor of chloride to stream water. Results suggest both fog and bedrock could be significant contributors to the chloride budget of these streams.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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 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".