Success factors and lessons learned during the implementation of a cooperative space for 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
It is largely documented that the exchange of information among critical infrastructures (CIs) is crucial to strategies involving the identification of their interdependencies and increasing their resilience. Based on the experience of the Centre Risque & Performance, Polytechnique Montréal (Québec, Canada), this paper presents the outcomes of a 15-year project that led to the development of DOMINO: a tool capable of identifying interdependencies among CIs and simulating potential domino effects of their failure. This paper illustrates how multi-organisational collaboration can help solve complex problems and shares lessons learned from the DOMINO initiative, which corroborates several observations documented in the literature. This paper suggests that, in order for effective and long-term collaboration to occur between CIs, not only must there be a sustainable governance framework in place, but upstream works must be conducted within these large organisations to encourage them to adopt, internally, more strategic, transversal and integrated risk management approaches.
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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 | 0.001 |
| 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