Numerical modeling: A complementary tool for studying CO<sub>2</sub> emissions from hydroelectric reservoirs
Bibliographic record
Abstract
In 1993, a vast study began on the production and emission of CO2 from hydroelectric reservoirs in central northern Québec. During the sampling field trips, information was collected about water temperature profiles, CO2 surface atmospheric concentrations, dissolved CO2 concentration profiles through the depth of the reservoirs, and CO2 fluxes at the surface and the bottom of the reservoirs, as well as many surface meteorological parameters. One of the goals of the project was to develop a mathematical model capable of simulating the physical processes responsible for the vertical transport of dissolved CO2 in hydroelectric reservoirs. This combined approach of measurements and numerical modeling confirmed certain hypotheses concerning the missing source of CO2, the existence of a spring peak of CO2 emission and an intense fall peak of CO2 emission for deep reservoirs. Moreover, a relation between differences in patterns of CO2 emission and reservoir depth was highlighted. It is shown that the numerical model developed in this research can be used to develop sampling strategies based on the characteristics of temporal and spatial distributions associated with each reservoir.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".