Bibliographic record
Abstract
This article considers the problem of diversity of the urban environment in terms of its visual (aesthetic) attractiveness.At the same time, the authors deliberately stepped away from the traditional views on diversity as a complex of a certain set of architectural forms and compositional means, regardless of the peculiarities of visual perception.The article considers the perception of urban development not as a static picture or frame, but in the process of movement.Movement, according to the authors of the article, is a source of detection and perception of spatial visual information, which makes the deep-spatial composition aesthetically attractive, shows its diversity.The criterion for assessing diversity has been offered -dynamic parallax, the speed of relative visual angular displacements of individual elements of the spatial structure during motion.Angular displacements are a source of dynamic perceived information -the basis of the diversity of buildings.It has been suggested that building on the basis of diversity alone can lead to chaos in development.According to the authors, it is necessary to combine monotony with diversity.The emotional potential of deep-spatial compositions, which provide smooth changes of informational flow has been substantiated, which is illustrated by the example of dynamic perception of the ensemble of the Round Square in Poltava (Ukraine).
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".