Chloride concentrations in Lake Tanganyika: an indicator of the hydrological budget?
Bibliographic record
Abstract
Abstract. On a historical time scale, this paper investigates the effect of hydroclimatic variations on the surface water salinity of Lake Tanganyika, the largest African lake and an open freshwater reservoir. Through annual water and chemical budgets, based on original and bibliographic data, a tracer of the water regime is proposed. Chloride, an inert and conservative element, seems to be the best candidate although its contribution to salinity is small; its use as a tracer of the water regime is validated on seasonal and historical time scales. Seasonally, a monthly water and chloride budget, constructed for an average year has been compared with data acquired in 1973. On a historical time scale, bibliographic data of chloride concentrations, compiled since 1939 have been compared with the level variation curve. The relation between lake level and surface water chloride concentration is significant on both time scales. Hence, the surface salinity/chlorinity of this freshwater lake is sensitive to hydroclimatic variations even if level variations are very limited in comparison with its great depth. This sensitivity is due mainly to the permanent thermo-haline stratification of the lake. Keywords: climate, water budget, hydrochemical budget, Lake Tanganyika, limnology, salinity
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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 | 0.001 | 0.002 |
| 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".