Bibliographic record
Abstract
The coffee shops paintings, in general, are the reflection of desires, interests, myths, and national and religious beliefs; meanwhile, they represent the ruling cultural spirit of the middle class in the urban community in Iran.This kind of painting has got its own special features and components which should be investigated in its own place, separately.One of the important aspects of these features is the aesthetic one which the current paper attempted to investigate.That said, the main purpose of the current study was to investigate the aesthetic features in the paintings of Hossein Gholler Aghasi.The main research questions were: How did the coffee shop painters use color to create artistic works?Did the painters pay attention to the concepts and effects of colors in their work?What colors have been used in coffee shop paintings and for conveying which concepts?How did the coffee shop painters use color and which components were included in their paintings?Moreover, in the current study, the combination of colors, the harmony of colors, the cold and warm colors, and their concepts, as well as the ratio of the function of colors to objects and geometric shapes were examined.The results of this thesis show that Agassi has a full understanding of the components and principles of linguistic, the concepts of colors, harmony, and the combination of different colors.Accordingly, in each of the types of coffee houses (Religious, Martial, and lyrical), the right harmony gives geometric shapes with appropriate colors and a decent character has been done through any 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 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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.974 | 0.975 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".