Technological and Compositional Features of the Interaction of Light Coatings with the Built Environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Today, in the design of the built environment the number of examples of using light materials and coatings is increasing. There are several types of materials that have completely different technological principles of action as the basis of their luminous properties but produce the same visual effect. Accordingly, this circumstance requires the differentiation of light coatings, depending on their technological features, followed by their combination into a single group in the analysis of the compositional features of the interaction of such coatings with the built environment. In the process of research it was found that technological features of the interaction of light coatings with the built environment consist in detecting their luminous properties when using radiation of different ranges of the optical spectrumultraviolet or visible. In this case, in both instances of interaction with the built environment, the following features of the visual composition are observed: increased contrast and color saturation; silhouette of composition elements; visual smoothing of gradual tone transitions; lack of influence of air perspective on color perception; visual perception of perspective due to physically moving objects further or with the help of the dimensional proportions of composition elements.
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.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it