Simulation and anticipation of domino effects among critical infrastructures
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
Interdependencies among critical infrastructures (CIs) are the cause of domino effects that may have serious consequences for society. To limit the consequences of these phenomena, it is important to be able to anticipate any situation that may trigger a domino effect. To do so, it is necessary to have a good understanding of how CIs are interlinked and how they rely on each other to properly operate. Once this achieved, a system must be put in place in order to model the possible propagation of domino effects and to alert the right people at the right time in order for them to take proper action. This paper presents a prototype of an early warning system (EWS) designed to anticipate and model the propagation of failures among CIs. Called DOMINO, this system makes it possible to rapidly visualise, in time and space, the propagation of a domino effect and to promptly identify the critical infrastructures potentially impacted. Along with effective communication systems, such tool can facilitate the exchange of relevant information between infrastructures operators and managers enabling them to put in place mitigation measures and to limit the consequences of domino effects.
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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