Cognitive Risk Control for Physical 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
The cognitive dynamic system (CDS) is a structured physical model and research tool inspired by certain features of the human brain. One such feature is the predictive adaptation of the organism to the future environment. From an engineering perspective, this property of the brain is of profound practical importance, particularly when the system, in the pursuit of goals or performing tasks, confronts unexpected adverse events or obstacles, which in the aggregate are commonly referred to as risk. To avert risk efficiently, much of the information processed in the past by the CDS is available for processing new information in one of the system's components termed the perceptor. In the face of uncertainty, the perceptor will provide the processed information to the executive in order for the latter to avoid probable risk. To that effect, the executive will be fitted with Bayesian filtering mechanisms that will guide the CDS to its goal through timely risk-avoiding actions. Those mechanisms not only have unique engineering applications but also potential value for understanding the predictive-adaptation property of the brain, which modern neuroscience attributes to the prefrontal cortex.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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