Bibliographic record
Abstract
The field of soft actuators and robotics has garnered considerable attention in recent years, driven by their distinct properties to adapt to diverse environments and enable secure and engaging interactions with humans. While current literature highlights a significant body of work on various soft actuators, it is noteworthy that the concept of soft sleeve actuation remains unexplored, as it has not yet been proposed. The concept of soft sleeve actuation represents a significant leap forward in the field of robotics, heralding tremendous potential for diverse applications, particularly for wearable robotics. This paper introduces a novel soft sleeve actuation mechanism, encompassing the development of two actuators capable of generating linear and bending motion. These actuators are lightweight and capable of generating considerable force and motion. Using Fused Deposition Modeling technology, a comprehensive fabrication framework was adopted to overcome manufacturing variability and fabricate high-quality airtight actuators. The mechanical performance of the proposed soft sleeve actuators (SLA) was investigated through a custom-built experimental testing setup. The impact of geometric parameters and material stiffness on the behavior of the developed actuators is studied and discussed.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".