Application of severity assessment tool (SAT) to 2008 midwest flood affected areas
Bibliographic record
Abstract
Critical infrastructure provides services to help support activities and functions of communities and industries. These activities/functions contribute socially and economically when performed efficiently in reliance with related critical infrastructure. During disasters, the critical infrastructure gets impacted and is unable to provide the full services which in turn affect the activities depending on that particular infrastructure. This reduces the contribution of the activities which results in impact on communities and industries. This research provides a unique perspective of preparing cities and industries against natural disasters in pre-, during and post-disaster situation. It is based on the inter-relationship that exists between communities, industries and related critical infrastructure. Identifying and fortifying infrastructure ahead of time will protect and support not only people and properties but also industrial activities and services. Moreover, it will become easier for governmental and industrial organizations to prepare mitigation plans and strategies that would help to prepare, prevent, respond, and recover from potential natural disasters. Thus, public agencies, industries and communities can largely benefit from natural disaster mitigation strategies that would help to speed up the recovery process as well as provide an
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".