Bibliographic record
Abstract
United Arab Emirates (UAE) is one of the developing countries that depend on hydrocarbon products in supporting its economy, where oil activities counted for 49.38 % of its total GDP (Gross Domestic Product) in 2009. Therefore, Abu Dhabi (AD), the capital of the UAE, has a vision where in 2030 the country will decrease its dependency on fossil fuel to 36% in order to stabilize the economy. Through AD strategy, a number of new industries have been planned to enter in order to diversify the economy. Some of the investments are believed to be a very high tech and innovation driven industries, such as the aerospace manufacturing industry. The aim of this paper is to analyze different countries' national systems of innovation, which have been selected based on literature where innovation is measured through number of KPIs (Key Performance Indices; R&D expenditures, number of research institutions, patents, number of engineers, new companies established, exports, etc). KPIs will be mapped from an innovation system perspective including the ones from UAE. Then a gap analysis will be conducted to determine where the country lags in terms of establishing a healthy national innovation system. A number of strategies will be suggested to enhance the UAE national innovation system
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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".