A patent analysis of hydrogen storage techniques in Taiwan: A preliminary study of the overall industry
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
Energy consumption is an essential issue for all human beings. With the emerging threat of environmental crisis, determining the most efficient and effective way to use the limited energy resources is becoming an urgent issue for the entire world. Hydrogen is one of the most well known energy alternatives. The difficulty of developing hydrogen storage technologies is one of the major factors hindering the widespread utilization of hydrogen energy in daily life. A study on technology development for hydrogen storage would have extraordinary value. The present study implements a deep and comprehensive patent analysis in order to identify the building blocks of hydrogen storage technologies. The scope of this study is limited to the countries most involved in developing hydrogen storage technology: the United States of America, Canada, Japan, and the European Union. By collecting data from major patent databases of each country, this study has accumulated a large amount of resources, which not only improve the comprehensiveness of this study but also help to generate valuable insights. With the results provided by this study, energy researchers can easily identify the most likely technology trajectory and improve the quality and usability of their research results.
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) | 0.000 | 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