Blockchain-Based Transparent Disaster Relief Delivery Assurance
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
Blockchain technology presents benefits that change the way business partners interact. This new way of establishing democratic trust encourages business owners to think differently. Disaster relief and aid industries are built on the power of collaborating participants. A very high number of participants in different hierarchies, including donors, charities, disaster victims, insurance companies and government agencies interact under extraordinary circumstances of a disaster and hard times. Establishing a new way of trust brings forward a better disaster recovery. In this paper, we propose a blockchain-based ecosystem. The blockchain-based disaster recovery not only would enhance the basic processes around disaster relief, but also promote the willingness of help by transparency and potential fraud prevention. This new blockchain system introduces an opportunity to be more resilient, to react rapidly, to communicate transparently, and to include new contributors such as IoT.
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 | 0.000 |
| 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 | 0.002 | 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