Hydrogen fuel cell electric trains: Technologies, current status, and future
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
Trains have been a crucial part of modern transport, and their high energy efficiency and low greenhouse gas emissions make them ideal candidates for the future transport system. Transitioning from diesel trains to hydrogen fuel cell electric trains is a promising way to decarbonize rail transport. That's because the fuel cell electric trains have several advantages over other electric trains, such as lower life-cycle emissions and shorter refueling time than battery ones, and less requirements for wayside infrastructure than the ones with overhead electric wires. However, hydrogen fuel technology still needs to be advanced in areas including hydrogen production, storage, refueling, and on-board energy management. Currently, there are several pilot projects of hydrogen fuel cell electric trains across the globe, especially in developed countries, including one commercialized and permanent route in Germany. The experiences from the pilot projects will promote the technological and economic feasibility of hydrogen fuel in rail transport.
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 | 0.000 | 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