Enhancing Supply Chain Resilience: the Impact of Blockchain & Emerging Technologies on Traceability
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
Supply chain traceability is an invaluable tool for companies to gain a competitive advantage today. The ever-changing global business environment, unpredictable market conditions, and changing consumer preferences call for agile supply chain systems. The pandemic helped reveal the vulnerabilities within the supply chain networks that need addressing. Various challenges, such as data reliability and integration, affect the current supply chain traceability and must be addressed. Such factors lead to inefficiencies within the system, which affect the process and lead to inconsistencies. The paper uses a systematic literature review to identify recent challenges and solutions to supply chain traceability. An analysis of blockchain technology's role in promoting transparency and security in supply chain systems was conducted. Lastly, an in-depth analysis of how improving traceability can help the supply chain networks build resilience.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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