Investigating the Applicability of Distributed Ledger/Blockchain Technology in Manufacturing and Perishable Goods Supply Chains
Bibliographic record
Abstract
Distributed ledger/blockchain has emerged as an important technology that can have a significant impact on the management of supply chains. This paper investigates the feasibility of adopting blockchain technology in both manufacturing and perishable goods supply chains. Two cases are used to illustrate the approach proposed in this work. The first case addresses the use of blockchain technology in the supply chain of composite materials in order to facilitate the certification process of components made of carbon fiber employed in the aerospace sector. The second case investigates the feasibility of adopting blockchain technology in the supply chain of live seafood. In the first case blockchain technology has the potential to be used by industry peers to perform experimental validation tests including flammability, crashworthiness, operational, etc. Additionally in both cases blockchain technology can be used for transportation, handling and storage, not to mention tamper proof checks, product history and provenance tracking.
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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".