A framework for completely separating the presentation and logic of Web-based applications.
Bibliographic record
Abstract
The use of the Internet and the World Wide Web (WWW) has grown at a phenomenal rate. The Web has become the solution for information exchange, user interaction and business processing. However, building dynamic, interactive and maintainable Web-based applications is not an easy task. Technologies currently used for Web presentation generation do not separate the presentation and logic. This requires people of two different skill sets to be involved at the same time, therefore applications are difficult to develop and maintain. In recent years, several frameworks have been developed to remedy the problem. But they all have some limitations and still cannot completely separate the application presentation from its logic. The current study attempts to provide an approach of completely separating the presentation and logic of Web-based applications by extending the traditional Model-View-Controller architecture. The research includes two parts. The first part provides a template language for representing Web pages containing dynamic contents without including application logic. The second part provides a framework that integrates the dynamically generated information with the predefined Web templates to generate Web page on the fly. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .N54. Source: Masters Abstracts International, Volume: 40-06, page: 1551. Adviser: Indra Tjandra. Thesis (M.Sc.)--University of Windsor (Canada), 2002.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".