Bibliographic record
Abstract
Nowadays Internet is more and more popular and having many influences with our life. We can use Internet in many fields to make our life become better. Thus, this research studies the application Internet to payment (Electronic Bill Presentment and Payment - EBPP) in order to help customers feel more comfortable and saving time. With EBPP, customers can check the bills online and fulfill the payment by Internet. Moreover, many papers talk about EBPP in United States, Canada, Europe, etc, but until now, no paper mentions deeply about EBPP in Vietnam – my country. It’s very good if Vietnam can apply EBPP model. It will open the new door for Vietnam to integrate into the world’s community. For this reason, this study attempt to analysis application EBPP model in Vietnam. Furthermore, this study also tries to feasibility study the ability to apply EBPP model of Vietnam. Finally, some suitable EBPP models were built to develop assessment and recommendations for Vietnam.
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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 | 0.001 | 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 | 0.001 |
| 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".