MagicDraw: Haptic-Assisted One-Line Drawing with Shared Control
Bibliographic record
Abstract
We present MagicDraw, a platform designed for force feedback guidance in one-line drawing. MagicDraw allows users to transition seamlessly between fully assisted sketching and freehand drawing through a control-sharing mechanism. The initial drawing concept is generated based on user input prompts. This platform operates similarly to tracing but introduces two major enhancements. First, MagicDraw provides force feedback guidance, aiding users in maintaining accurate line-following. Second, the system enables dynamic control sharing, allowing users to deviate from the predefined path and engage in creative exploration. We also introduce “exploration region,” where users can perform freehand drawing. In these regions, the predefined path advances outside the boundary, pausing for the user’s creative deviations. As the user returns to fully assisted sketching, these regions shrink until the user resumes force feedback-guided tracing. This approach ensures users can explore creative variations while still receiving structured guidance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".