Integrating flying and fish tank metaphors with cyclopean scale
Bibliographic record
Abstract
In fish tank VR environments, the screen is used as a window into a virtual environment. This effectively creates a useful 3D workspace in the vicinity of the monitor screen, near to the user. However, many geographical applications require the user to cover large virtual distances and to support this a flying interface is often provided. The authors describe a method for combining the flying and fish tank metaphors to create a practical working environment. The central insight developed in the paper is that a geometric transformation that they call the "cyclopean scale" enables the simple combination of flying and fish tank VR interaction metaphors. Cyclopean scale continuously scales the working environment to lie just behind the screen in terms of stereoscopic depth. Cyclopean scale allows for fish tank VR viewing and also places objects at a convenient distance for manipulation, optimizes stereo display parameters and reduces stereo display problems (vergence focus conflict). They have implemented this technique in a system called Fledermaus VR with a cable route editing task. This is an application for planning the layout of submarine cables.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".