Analysis Of Energy And Water Options For A Recreational Property Located In Lac La Nonne, Alberta
Bibliographic record
Abstract
This paper analyzed the water and energy options for a recreation property located at Lac La Nonne, Alberta. Optimum water and electricity sources were chosen based on the total cost of ownership over a twenty year period, with the costs adjusted to present value, using an inflation rate of 4%. The costs were based on vendor quotes, which were assumed to be correct. If the cheapest option had a significant, negative impact on the environment, or required a considerable amount of maintenance over and above what the average individual is willing to undertake, the next cheapest option would have been considered. In the case of the options analyzed, the cheapest options had no significant environmental issues or maintenance considerations. In the case of water, it was determined that a well was the least expensive and most environmentally friendly option, offering both a significant cost savings over a twenty year period, as well as a reduced impact on the environment over the use of a cistern. In the case of electricity, it was determined that non-renewable, grid supplied power would be the cheapest source of energy. The paper also considered the heating options. Gas powered furnace, passive solar thermal and wood stove are all considered. Given that the property will be used primarily over the summer months, there are limited heat requirements for the property. As a result, the gas powered furnace is not considered a cost effective energy source. Heat will be supplied through passive solar thermal incorporated in the building design. This heat source will be supported by a wood stove in the home. Finally, consideration is given to the energy required to heat hot water for the building. Given that a decision was made not to bring natural gas to the subject property, and to use electricity sourced from the grid, the most cost effective means of heating the hot water is through an electric hot water heater. Should an alternate source of energy have been chosen, there may have been a better option for the heating of hot water, such as solar thermal.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".