Bibliographic record
Abstract
Abstract A new architecture for a thin (2‐cm depth) rear projection display is described. In order to achieve this small depth, a very high density of rear projectors is used. Three prototype displays using rear projectors on both 5‐ and 2‐cm pitch arrays are described. The displays can achieve an effective screen pixel pitch of as small as 0.5 mm, which makes this technology competitive in terms of resolution with fine pitch LED displays; however, orders of magnitude fewer LEDs are required: Each rear projector requires only one white LED and a color liquid crystal light modulator. In the three prototypes, the projector light modulators utilize 101‐cm (40 in.), 80‐cm (31.5 in.), and 60‐cm (24 in.) diagonal liquid crystal display glass. To minimize cost, no lenses are utilized for the rear projectors. An RGB LED array may augment the projector array, which provides a low resolution component of the image onto which the high resolution component is superimposed by the projector array. Edge gaps between active areas on adjacent LCD glass units are completely eliminated by the rear projection approach enabling low profile wall‐size seamless displays. Display contrast depends on rear projection screen design.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".