Technological and Compositional Features of the Interaction of Light Coatings with the Built Environment
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.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".