ADVANCES IN RESERVOIR GREENHOUSE EFFECTS AND PRINCIPAL INFLUENCE FACTORS ANALYSIS
Bibliographic record
Abstract
Global climate warming resulted from greenhouse gas emission already has attracted more and more attentions from governments and the public all over the world.At present,the status of greenhouse effect from large freshwater reservoirs in global climate warming became a debated issue in the academic community around the world gradually.The previous studies showed that some reservoirs for hydro-electronic generation or other purposes in Canada,U.S.A,Brazil and other counties would release additional greenhouse gas(CO2 and CH4)into atmosphere due to the inundation of soil and vegetation in reservoir area as a result of the construction and impoundment of reservoir.In this paper,an overview of greenhouse effect of reservoir on the global warming was addressed in order to understand the advances in greenhouse gas researches at home and abroad.It should be illustrated that some key issues,including observation of reservoirs greenhouse effect,case studies,the inner mechanism,emission processes and main influence factor of greenhouse gas from reservoirs,wese discussed and summarized for the sake of obtaining more information about the emission of greenhouse gas from freshwater reservoirs and providing constructive guide for hydro-electronic development in China.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".