Bibliographic record
Abstract
Current world energy consumption is dominantly (87%) supplied by non-renewable resources (coal, oil, gas, uranium). On the long-term these non-renewable energy sources will have to be substituted. This combined with concerns over greenhouse gas emissions has enhanced interest in renewable energy supply. Geothermal energy currently provides only a minor component of world energy, although for some countries it forms a significant contribution to national energy needs. Of all the renewable resources, geothermal has some of the most significant potential. Recent technological advances has reduced the temperature required for power generation which in turn reduces the depth required to access the resources as well as broadens the area where the resource is assessable. Although used extensively throughout the world, geothermal energy has not been significantly developed to date in Canada. Still historic work and pilot projects by the National Geothermal Program from 1975 to 1985 has shown Canada has regions of high potential. New work has focused on compilation of historic data and national-scale mapping of key geothermal parameters to help better define regions best suited for exploration activity. Sedimentary basins of Canada have many regions that hold high temperature waters that could produce electricity from co-produced fluids. This presentation will provide an overview of the various geothermal energy resources and potential uses in Canada.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".