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
Serious problems with bridging multiple scales in the scope of a single numerical model make computer simulations too demanding computationally and highly unreliable. We present a new concept of modeling framework that integrates the particle method with graph dynamical systems, called the particle automata model (PAM). We assume that the mechanical response of a macroscopic system on internal or external stimuli can be simulated by the spatiotemporal dynamics of a graph of interacting particles representing fine-grained components of biological tissue, such as cells, cell clusters, or microtissue fragments. Meanwhile, the dynamics of microscopic processes can be represented by evolution of internal particle states represented by vectors of finite-state automata. To demonstrate the broad scope of application of PAM, we present three models of very different biological phenomena: blood clotting, tumor proliferation, and fungal wheat infection. We conclude that the generic and flexible modeling framework provided by PAM may contribute to more intuitive and faster development of computational models of complex multiscale biological processes.
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