تجربة دولة قطر في تطوير صناعة الغاز الطبيعي وامكانية الاستفادة منها في العراق [Qatar's Experience in the Development of the Natural Gas Industry and the Possibility of Benefiting From it in Iraq]
Bibliographic record
Abstract
The natural gas is one of the most important resources for energy, and in a lot of countries it becomes the main second resource after oil, We can notice that there is a rising in depending on natural gas in a lot of social and industry sectors, In 2009 the International reservation from natural gas was more than (187 Billion Quebec Meter), The experiment of Qatar in producing and industrialization of natural gas was one of the most successful experiments in the world, Qatar become at the third stage internationally in the reservation of Natural Gas and it's producing was rise from (27 Billion Quebec Meter) in 2001 to (77 Billion Quebec Meter), also the producing of liquid natural gas was rising from (18,6 Billion Quebec Meter) in 2002 to (41,84 Billion Quebec Meter) in 2007 and in this quantity Qatar become the first internationally in producing and exporting liquid natural gas.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.136 | 0.120 |
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".