Bibliographic record
Abstract
Haptic Holography, was perhaps, first proposed by workers at MIT in the 90s. The Media Lab, headed up by Dr. Stephen Benton, with published papers by Wendy Plesiak and Ravi Pappuh. −1 Recent developments in both the technology of digital holography and haptics have made it practical to conduct further investigations. Haptic holography is auto-stereoscopic and provides co-axial viewing for the user. Haptic holography may find application in medical & surgical training and as a new form of synthetic reality for artists and designers. At OCAD's PHASE Lab (Prototypes for Holographic Art and Science Explorations) workers are exploring hybrid forms of augmented reality, that combine haptics, interactivity and auto-stereoscopic imagery. Conventional Haptic environments, while presenting a 3D physics environment, typically provide a 2D visual work/play space. Orienteering in such an environment creates an uncertain spatial relationship for the user. Our group creates 3d models from which we create holographic constructs. The same model is used to create the physics environment. The two models are super-imposed. The result: Holograms you can touch.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".