Developing Engineered Geothermal Systems (EGS) in Alberta, Canada
Bibliographic record
Abstract
The extraction of hydrocarbon, minerals, or geothermal resources requires extensive subsurface characterization. This process balances both locating the highest concentrations of the resource and assessing where there is a demand for those resources. In the context of the geothermal exploration being undertaken by Helmholtz Alberta Initiative (HAI), this requires that heat sources for heavy oil and bitumen production are found close to the deposits. This focuses exploration on the regions of the largest oilsand and heavy oil deposits around Lloydminster, Cold Lake, Peace River, and Fort McMurray in Alberta province, Canada (ERCB, 2010; Hein, 2006). In addition, bitumen production from the Grosmont carbonate trend (Schmitt, 2011a; b) that lies about 100 km to the west of Fort McMurray may also require large amounts of thermal energy. In all of the above applications, the geothermal energy has the potential to greatly reduce the environmental footprint of oilsand extraction. This occurs by generating heat with geothermal plants, and not burning natural gas. Heavy oil production is not the only potential consumer of energy in Northern and Central Alberta. The forestry industry also uses large amounts of thermal energy in the production of paper. Further, there are numerous isolated First Nations communities who could use geothermal energy to replace the expensive practice of transporting fuel for generators.
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.
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 | 0.000 |
| 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".