Bibliographic record
Abstract
Architectural visualizations based on renderings<br/>from 3D models have developed dramatically in the<br/>past two decades. Increased computational power<br/>and advanced render engines have speeded up the<br/>rendering process and the automation of many<br/>render settings and accessories have made photo-real<br/>rendering accessible to a larger group of users than<br/>the previous exclusive group of tech savvy render<br/>pioneers.<br/>This paper presents an analysis of architectural<br/>visualizations based on their level of realism as<br/>well as their openness to interpretation to guide in<br/>choosing the right abstraction for visualizing and<br/>communicating architectural projects at any stage in<br/>the design process.<br/>Core elements of the photo-real visualization and<br/>its impact on perception and interpretation are<br/>described and explains why focus has shifted within<br/>recent years from aiming solely at the photo-real<br/>towards an addition of artistic abstraction in teaching<br/>visualization of early designs, concepts and visions.<br/>Selected visualizations from the undergraduate<br/>courses in digital architectural representation are used<br/>as examples.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads 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".