Comparative Evaluation of Display Technologies for Collaborative Design Review
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
The effectiveness of five display technologies for supporting a collaborative workspace design review was compared. Participants searched for design flaws in a model of the front dashboard of a vehicle including an in-vehicle navigation system. The display types were 2D CRT, 3D CRT, 3D via Curved plasma display, a large DataWall display, and a cave automatic virtual environment (CAVE). Detection accuracy, time, and usability measures were obtained. The results indicated that detection accuracy was higher for 3D CRT and Curved displays than the 2D display or more immersive DataWall and CAVE displays. Additionally, a speed-accuracy trade-off was observed such that detection time was longer for 3D CRT and Curved displays than for 2D, or the more immersive displays. Subjective measures revealed that participants' comfort and confidence level was lower with the 2D displays than the 3D displays. Lack of sufficient training time is likely to have affected detection accuracy with the more immersive 3D displays. Overall, the use of the 3D CAD model on a standard CRT or a Curved display was the most cost-effective for collaborative design review.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it