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
FCMs are aimed at modeling and simulation of dynamic systems. They exhibit numerous advantages, such as model transparency, simplicity, and adaptability to a given domain, to name a few. FCMs have been applied to numerous industrial and research areas. In some cases generic FCMs suffer from a certain drawback that originates from their definition and concerns a limited, first-order dynamics of processing realized at the nodes of the maps. In this study, we introduce a concept of higher-order memory based FCMs. The proposed extension modifies the simulation model of a generic FCM while it does not negatively impact transparency and simplicity of the model itself. We discuss several architectural alternatives along with the ensuing computing and optimization aspects. Preliminary experimental results included in this paper show superiority of the extended higher-order memory based FCMs over a generic FCM in terms of the modeling accuracy
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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