Bibliographic record
Abstract
Abstract The potential for innovativeness is difficult to measure, though many have attempted to do so. In order to look at Poland’s innovation potential, its current position and its opportunity to grow, compared with developing and developed countries, this study analysed the patent statistics of the Polish and European Patent Offices. Poland has been a member of the European Union for over a decade now. Therefore, we took into consideration the statistics for patent applications and grants for the last decade, up to the first quarter of 2016. The questions we wanted to answer concerned not only the technology fields that Poland patented its inventions in, but also the types of patent grantees and applicants. In order to determine why Poland is still considered to be only a moderate innovator by the Innovation Union Scoreboard, we also gathered information on Polish inventors abroad in 2015 and the first quarter of 2016, to see their number, technology fields, and types of patent grantees. Finally, we attempted to identify the main barriers that seem to inhibit Polish technology and innovation growth, despite significantly growing R&D intensities (up from 0.56 GDP and EUR 1,139 M in 2004 to 0.94 GDP and EUR 3,864 M in 2014).
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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 | 0.001 | 0.001 |
| 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".