Bibliographic record
Abstract
The following report is based on the fact that we today aren´t building enough small apartments with the right of tenancy around the country. Numbers show that many young people and students will be in need of an apartment in the upcoming years. Because we already have a lack of small apartments in many of the student cities we have to find a solution today. Could module apartments be the solution? The report is a part of a project, which with the help of industrial building and its prerequisites, smaller apartments in module form has been planned. The apartments, are as far as possible, standardized but concludes a flexibility in the shaping which creates possibilities for different solutions. The apartments can be combined in different ways for use at different sites. In the project the quarter Järnbäraren has been used as a plot example, where the apartments have been used as student housing. The report describes the theoretical reasons to why you should use industrial building and what it takes for it to be a successful concept. It also contains analysis of earlier projects which can be compared with this one. The report also includes historical aspects on the development of industrial buildings during the 20th century and how the housing market has changed over the past years. The report shows the thoughts and speculations that lies behind the decisions which have been made during the project. It also works as a description of the prerequisites in the project. Most prerequisites came from the company Moelven, who there have been a cooperation with since the start of the project. The result has shown that it is possible to develop module apartments with high quality despite standardization and cost conscious thoughts. Since it is the technical parts in the apartment that is the biggest cost for the module, you’re able to increase dwelling space improve the quality in the apartment without the rent being raised and be absurd for example students.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.475 | 0.426 |
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".