A system of systems approach to disaster management
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
Disaster situation management involves managing information and resources to tackle time varying situations surrounding a geo-spatial region of interest. Post disaster, relief and recovery operations are handled in a distributed self-configuring manner and involve a diverse array of resources and participants. Although in-situ planning is the only option, disaster situation management should consider system requirements, processes and interdependencies to make the process effective. Having a higher level view of the system, its requirements and the evolving situations warrant the need for accurate models; models that are able to predict, forecast and deal with the logistical, technical, operational, and financial challenges. We propose a system of systems approach to situation modeling to represent the causal relationships between resources, functional assets and different stages in the infrastructure renewal process. Generic interactions at the situation and system level have been defined and theory is developed for the use of fuzzy graphical models. A genetic algorithms based technique has been developed to determine optimal structure and parameters of the graphical model. Real world data from a post earthquake reconstruction process is used to validate the effectiveness of the proposed method.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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