Spatial analysis of hydrogen production from renewable energy sources for injection in natural gas grid. Canada case study
Bibliographic record
Abstract
The purpose of the study is to localize sites for the production of hydrogen from renewable energy sources (RES) and its injection in the natural gas transport network. The study is performed with Geographic Information System (GIS) based analysis. The first step is the analysis of GIS data on RES potential power production in Canada, in particular for wind and solar PV. The results are extracted and the power potential obtained is transformed in potential production of hydrogen with electrolysis. The results are disposed on the map and spatial criteria are used to identify the production hubs. In particular the main criteria are the production potential and the distance of the sites from the natural gas network. Different analysis are performed by changing the quantity of hydrogen to produce to satisfy different levels of injection in the natural gas grid. The GIS software used in the analysis is ArcGis, in the ArcMap 10.6 version.
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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 | 0.000 | 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 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".