The preventive approach to risks related to interdependent 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
Life Support Networks (LSNs) are those entities that provide society with essential resources such as energy, telecommunications, etc., in order to assure its correct functioning. Thus, the correct functioning of LSNs guarantees the correct functioning of society. However, the growing complexity of LSNs and their interdependencies reveal new vulnerabilities. These interdependencies are a true means of propagation of hazards between networks. The current methods of risk management (often based on probabilistic approaches, analyses of worst case scenarios and/or aiming at the modelling of the interdependencies) are hardly applicable to the concrete realities of complex and dynamic systems such as LSNs. To compensate for these gaps, the Centre risque & performance has developed, jointly with multiple partners, a new proactive method of risk management based on the prevention and the anticipation of harmful consequences that would affect LSNs. In this paper, we present this methodology and its operational tools.
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 | 0.001 | 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 | 0.001 | 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