A brief technical note on haptic jellyfish with Falcon and OpenGL
Bibliographic record
Abstract
The ultimate goal of the project is to have a fully-tangible 3D interactive responsive jellyfish character, a work inspired by nature. We begin with a real-time physically simulated 2D prototype jellyfish that swims about and classically the users can just "drag" it around using a mouse. This work augments the interaction model with the attachment of the Novint Falcon haptic device that the jellyfish itself can "move" through the calculation of internal forces as we accumulate them for each of its particles, one of which serves as a guide particle to send the force coefficients to Falcon. The idea is to "feel" the weight and push of the jellyfish as it moves along and interact with it to change its direction. The subsequent work will focus on augmenting the bell of the jellyfish to 3D and more realistic tentacles. All are done in affordable Falcon and OpenGL. The jellyfish itself is based on the elastic real-time two-layer softbody simulation framework.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".