The Impact of Export Volume and GDP on USA’s Civil Aviation in Between 1980-2012
Bibliographic record
Abstract
This paper assays how the effect of USA’s both export volume and GDP have on civil aviation by implementing econometrical models such as linear regression and Johansen Co-integration tests in order to realize the dimension of its influence. The impact of both export volume and GDP on civil aviation have analyzed between the years 1980 and 2012 in order to make it a parametrical test by using E-Views Programme. According to Johansen cointegration test there is a long term relationship between the variables in between 1980-2012.Furthermore, It has been founded that USA’s export volume and GDP have crucial influence on civil aviation according to the E-Views programme results within the periods of 1980-2012. influence. The impact of both export volume and GDP on civil aviation have analyzed between the years 1980 and 2012 in order to make it a parametrical test by using E-Views Programme. According to Johansen cointegration test there is a long term relationship between the variables in between 1980-2012. Furthermore, It has been founded that USA’s export volume and GDP have crucial influence on civil aviation according to the E-Views programme results within the periods of 1980-2012.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".