Yukon 2115: A Futuristic City Design with a Geological Twist
Bibliographic record
Abstract
Current trends in anthropogenic greenhouse gas emissions and global warming show no indication of halting in the near future. Assuming that these trends continue up to the year 2115, it will become necessary to design a city which is adapted for the anticipated changes to the environment. In the Yukon Territory, terrain will change based on fluctuations in wind speeds, permafrost levels and precipitation, which in turn affects surface water routes. The technology available will also be more advanced, and it is possible that sustainable sources of energy will be more popular as well as economically feasible. In order to integrate all of these geological, environmental and economic factors into one project, a city will be designed and modelled in the Yukon Territory for the year 2115. The design will be consider forward modeling of local climate change, precipitation, surface water routes and permafrost levels. The city will be designed to be sustainable, affordable, and have limited negative environmental and social impacts. Using this information, it will be modelled using the programs ArcGIS and SimCity and geological models may also be generated using geomechanical software such as Slide. The city will implement a zero waste program and employ one or more of three sustainable energy sources: nuclear fusion, geothermal and solar power. The main industry of the city will be four lead-zinc deposits in the Selwyn Basin, on the eastern edge of the territory; it will provide jobs and a stable economy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".