Information Processing for Analysis of Consumption Flexibility of Global Natural Gas Demand
Bibliographic record
Abstract
Gas consumption exist great regional difference, price and income are the main factors affecting consumption .Global gas consumption has slow growth, but the price in 2008 there was a twist. We analyze the global natural gas consumption and price points using the data from the BP. The level of economic development and natural gas reserves determine the differences in the levels of consumption. In order to eliminate the impact per unit, the regression model uses the data in the log. This paper studied the influence factors of natural gas consumption in North America using of consumer income elasticity and price elasticity. The results show that the gas consumption have a low income elasticity and price elasticity is higher .Law of "S" shape can explain the income elasticity is low, the reason is that the stage of economic development. Price elasticity is higher lies in the different between Canada and the United States, the United States is a net importer of natural gas, and Canada is a net exporter. Keywords: Consumption Flexibility; Natural Gas Demand; income; price
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".