Bibliographic record
Abstract
The subsurface temperature field beneath Winnipeg, Canada, is significantly different from that of the surrounding rural areas. Downward heat flow to depths as great as 130 m has been noted in some areas beneath the city and groundwater temperatures in a regional aquifer have risen by as much as 5°C in some areas. Numerical simulation of heat transport supports the conjecture that these temperature changes can be largely attributed to heat loss from buildings and the temperature at any given point is sensitive to the distance from and the age of any buildings. The effect is most noticable when buildings are closely spaced, which is typical of urban areas. Temperature measurements in areas more than a few hundred meters away from any heated structure were only a few tenths of a degree Celsius greater than those observed outside the city, suggesting that other reasons for increases in subsurface temperature, such as changes in surface cover or climate change, may be responsible for some of the some of the observed increase in temperatures. These sources of additional heat to the subsurface make it difficult to resolve information on past climates from temperatures measured in boreholes and monitoring wells. In some areas, the temperature increases may also have an impact on geothermal energy resources. This impact might be in the form of an increase in heat pump efficiency or in the case of the Winnipeg area, a decrease in the efficiency of direct use of groundwater for cooling.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".