Bibliographic record
Abstract
With a declining mining industry, Canada is looking for new models of economy. Arctic Eco-Tourism has already started growing over the last decade and is expected to grow even more rapid in future. This brings the chance of economic growth and employment. But it is also a danger¬ous situation for nature. Since the Canadian north is to more than 98% untouched, uncontrolled growth of traditional building complexes must not destroy nature as is already did in the south. The concept suggests combining two aspects of Canadian past with one of the future. The declared goal is not to destroy any more nature by infrastructure of insensible build-ings for tourism. The site of the Diavik Diamond Mine has been chosen for two things: First, to re-naturalize the area by money made from tourism. Second, to build an invisible starting point for Eco-Tourism in this area. The huge holes, which have been the result of a process called open-pit-mining, are a perfect spot to implement a building on a site from which nature was already banished. Another main point is to use the old airfield as infrastructure for tourism. No additional streets need to be built. The aim is to create a resource efficient and fully autocratic building complex for arctic Eco-Tourism. This complex will mainly offer temporary accommodation for tourists. It is the goal to use this project to examine the opportunities with robotically fabricated CLT structures as prefabricated building parts.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".