Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Imitating nature's mechanisms offers enormous potential for the improvement of our lives and the tools we use. This field of the study and imitation of, and inspiration from, nature's methods, designs and processes is known as biomimetics. Artificial muscles, i.e. electroactive polymers (EAPs), are one of the emerging technologies enabling biomimetics. Polymers that can be stimulated to change shape or size have been known for many years. The activation mechanisms of such polymers include electrical, chemical, pneumatic, optical and magnetic. Electrical excitation is one of the most attractive stimulators able to produce elastic deformation in polymers. The convenience and practicality of electrical stimulation and the continual improvement in capabilities make EAP materials some of the most attractive among activatable polymers (Bar-Cohen Y (ed) 2004 Electroactive Polymer (EAP) Actuators as Artificial Muscles—Reality, Potential and Challenges 2nd edn, vol PM136 (Bellingham, WA: SPIE Press) pp 1–765). As polymers, EAP materials offer many appealing characteristics that include low weight, fracture tolerance and pliability. Furthermore, they can be configured into almost any conceivable shape and their properties can be tailored to suit a broad range of requirements. These capabilities and the significant change of shape or size under electrical stimulation while being able to endure many cycles of actuation are inspiring many potential possibilities for EAP materials among engineers and scientists in many different disciplines. Practitioners in biomimetics are particularly excited about these materials since they can be used to mimic the movements of animals and insects. Potentially, mechanisms actuated by EAPs will enable engineers to create devices previously imaginable only in science fiction.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it