DEVELOPING AN INNOVATION AND TECHNOLOGY TRANSFER E-TOOL IN THE FIELD OF BIO-ECONOMY
Bibliographic record
Abstract
The way business is conducted, the way people live, work, socialize and meet have changed dramatically in the past quarter century, and more so in the past decade, due to the development of digital innovative solutions. From the internet to smartphones, from 3D printing to social media, technology is creating an environment that is interactive, integrated and available for everyone. The paper presents an online e-tool that will help create bridges between SMEs, research institutes and public authorities in the Danube area. Creating this platform for the development of innovative solutions facilitates the communication and collaboration of actors in the Danube Region, with multiplying effects in the field of bio-economy. The platform increases the possibilities of creating innovative products by making explicit the mechanisms through which the market in the bio-economy sector works, thus leading to the attainment of sustainable solutions for the Danube Region.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".