Mapping and Quantitative Analysis of the Main International Standards of the Hydrogen Chain as an Energy Vector
Bibliographic record
Abstract
The safe and efficient implementation of hydrogen as an energy vector is related to international standards that standardize its production, storage, transportation and application. These regulations are essential to guarantee the safety, efficiency and interoperability of technologies associated with hydrogen, enabling their insertion into the global energy scenario. This article analyzes the regulation of the hydrogen value chain as a sustainable energy carrier. The standards were classified by Organization, Area, Application, and Objective, as well as thirteen other subcategories. The results indicated a predominance of standards from the China National Standards (GB) organization, with a focus on Fuel Cells (FC), Equipment (EH), and Constructive Aspects (CA). The International Electrotechnical Commission (IEC) focuses on Fuel Cells (FC), Performance (PE), Stationary Plants (SP), and Equipment (EH), while the Canadian Standards Association (CSA) stands out in Vehicle Refueling Stations (VR), Equipment (EH), and Constructive Aspects (CA). Additionally, the International Organization for Standardization (ISO) shows a uniform distribution, with a moderate emphasis on VR, Materials, Accessories or Others (OR), and Equipment (EH).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".