A Framework for Analyzing and Creating Self-assembling Systems
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
Self-assembly is an emergent property of decentralized systems, which is seen throughout nature. Understanding and applying this emergent property continues to be an important subject in the natural sciences, as well as engineering and computer science. However, only the specific principles and mechanisms of self-assembly are considered within the scope of their respective disciplines. A framework is presented here, which abstracts self-assembly to components, environment, energy, assembly protocol, spatial relationship, localized communication, and rule set. By viewing self-assembly in this manner, this framework facilitates melding the various self-assembly principles and mechanisms studied across disciplines. The benefit of this is that it aids in the pursuit of designing synthetic systems mirroring the robustness of this bottom-up construction process in nature. Several experiments are presented that exhibit this robust construction process, and demonstrate how this framework can be leveraged for analyzing and creating self-assembling systems.
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