Knowledge and technology transfer from research organisations to businesses
Bibliographic record
Abstract
<p dir="ltr">The development of an innovative economy depends on the ability to use the achievements of science and the possibility of their distribution. The book is part of an extremely important discussion on improving the innovativeness of the Polish economy by improving cooperation between the science and business sectors. The authors diagnose the situation of Polish universities in the field of commercialization of research results and cooperation with business, examine various groups of stakeholders participating in professional processes of knowledge and technology transfer in Poland, Norway, France, the Czech Republic, Hungary, as well as in the USA and Canada. They analyse studies of good practices - both Polish and foreign - in order to present recommendations for necessary changes for universities in the area of shaping good relations with enterprises in order to increase the innovation potential and increase the competitiveness of the economy. <p dir="ltr">Originally published as <i>Transfer wiedzy i technologii z organizacji naukowo-badawczych do przedsiębiorstw</i> (University of Lodz, Poland, 2016).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.367 | 0.012 |
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; both teacher heads agree on what is shown here.
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".