HIGH-TECH INDUSTRY CLUSTERS: EXAMPLE OF AVIATION CLUSTERS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing competition with globalization has increased the need for strategies and tools that will create competitive advantage. The cluster concept put forward by Porter has been generally accepted in the political field, business world and academic circles, and its applications have spread all over the world. High-tech industry; It is distinguished from other industrial branches with its characteristic features such as relying on intense R&D, requiring the use of tacit knowledge that includes know-how, continuity in innovation, use of intensive technology and technological knowledge in production processes. The aviation industry is a high-tech industry, consisting of production networks spread all over the world and generally located regionally. Seattle, Toulouse, Montreal, Bangalore is being accepted as the world's largest aviation clusters HUKD, ESAC, OSSA, BASDEC and TSSK that they clustered aviation in Turkey.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it