Trends in worldwide nanotechnology patent applications: 1991 to 2008
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
Nanotechnology patent applications published during 1991-2008 have been examined using the "title-abstract" keyword search on esp@cenet "worldwide" database. The longitudinal evolution of the number of patent applications, their topics, and their respective patent families have been evaluated for 15 national patent offices covering 98% of the total global activity. The patent offices of the United States (USA), People's Republic of China (PRC), Japan, and South Korea have published the largest number of nanotechnology patent applications, and experienced significant but different growth rates after 2000. In most repositories, the largest numbers of nanotechnology patent applications originated from their own countries/regions, indicating a significant "home advantage." The top applicant institutions are from different sectors in different countries (e.g., from industry in the US and Canada patent offices, and from academe or government agencies at the PRC office). As compared to 2000, the year before the establishment of the US National Nanotechnology Initiative (NNI), numerous new invention topics appeared in 2008, in all 15 patent repositories. This is more pronounced in the USA and PRC. Patent families have increased among the 15 patent offices, particularly after 2005. Overlapping patent applications increased from none in 1991 to about 4% in 2000 and to about 27% in 2008. The largest share of equivalent nanotechnology patent applications (1,258) between two repositories was identified between the US and Japan patent offices.
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 | 0.001 | 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 it