Bridging the gap between RFID/EPC concepts, technological requirements and supply chain e-business processes.
Bibliographic record
Abstract
Supply chain pressures have caused some firms to reexamine their processes.In doing so, firms are exploring emerging technology such as RFID to enable seamless exchange of information within their supply chain.While RFID promised to "revolutionize" the way business processes are managed today, the impact and benefits of the technology are still unclear and ambiguous concepts such as "intelligent products", "smart supply chains" or "the internet of things" are still creating confusion within potential adopters.In this paper an attempt is made to (i) clarify the ambiguity surrounding RFID vs. other AIDC and IOS technologies such as the EPC Network (ii) specify the technology readiness & IT related requirements of actual and emerging applications, and (iii) propose a framework to highlight how the technology can be used to support RFID/EPC enabled ecommerce processes and support practitioners and academicians in assessing the impact of RFID on electronic supply chain business processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".