A Study on Applications of Housing Interior Design Elements according to the Sensibility Type
Bibliographic record
Abstract
The purpose of this study was to draw application elements of housing interior design according to user-oriented sensibility types. The sensibility evaluation experiments were conducted to target the general user 118 people using the sensibility evaluation tool for housing interior space. The results of the analysis were as: To produce the 'cozy' space, the colors and materials giving soft and natural feeling should be used. For the 'practical' space, type of ceiling and window that give the visually open feeling, the user-oriented furniture arrangement that allows using the space efficiently. For the 'cheerful' space, the simple and natural effects should be produced by using closed space that stable. For the 'traditional' space, the natural fishing material having rough texture should be used. For the 'unique' space, the space contained the dynamic feeling by the diagonal or vertical line and the graphic expression in the wall. For the 'congenial' emotional space, basic is the symmetric, stable and simple space. On the other hand, for the material, small size, natural texture or typical and soft materials should be used. For the 'sensuous' space, the dynamic and vertical sense of space should be expressed by the type of ceiling. The most important elements for the space of 'gorgeous' sensibility, is the color.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".