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
As blockchain technology is becoming a driving force in the global economy, it is also gaining critical acclaim in the e-commerce industry. Both the blockchain and e-commerce are inseparable as they involve transactions. Blockchain protect transactions and e-commerce activities rely on them. Blockchain technology enables a decentralized marketplace to support important business activities like secure payments, managing the supply chain and reducing the fraud to mention few. In this special issue editorial we are introducing 11 research articles in this hot area of research that were selected by our reviewers from over than 250 submissions. As blockchain technology is becoming a driving force in the global economy, it is also gaining critical acclaim in the e-commerce industry. Both the blockchain and e-commerce are inseparable as they involve transactions. Blockchain protect transactions and e-commerce activities rely on them. Blockchain technology enables a decentralized marketplace to support important business activities like secure payments, managing the supply chain and reducing the fraud to mention few. In this special issue editorial we are introducing 11 research articles in this hot area of research that were selected by our reviewers from over than 250 submissions.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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