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
Biomimetics, as the transfer of strategies from biology to technology, is an emerging research area and has led to significant concepts over the past decades. The development of such concepts is described by the process of biomimetics, encompassing several steps. In Practice, beneficiaries of the process face challenges. Therefore, to overcome challenges and to facilitate the steps, tools have been developed in various areas, such as engineering, computing and design. However, these tools are not widely used yet. This paper presents an overview and a classification study of more than 40 tools with qualitative criteria. The criteria included, for example, the year of development, the accessibility of tools, the facilitated steps of the process or their contribution to sustainability. The classification shows that certain steps of the process and their challenges are well addressed by the tools, while other steps are not. The presented results contribute to the proposal of an improvement of the state of the art, and they build the foundation for future theoretical and practical analyses. These findings could contribute to increasing the implementation of biomimetics in various disciplines in the long term.
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) | 0.000 | 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