An efficient dual caching strategy for web service-enabled PDAs
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
PDAs have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. However, the most significant step in the evolution of PDAs was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity like email, web browsers and maybe most importantly smart/rich clients. Being able to host smart clients allows the users of PDAs to seamlessly access the IT resources (e.g. legacy apps) of their organizations. One increasingly popular way of enabling access to IT resources is by using Web Services (WS) [14]. This trend has been aided by the rapid availability of Web Service (WS) packages/tools, most notably the efforts of the Apache group [1] and IDE vendors (e.g., Microsoft's Visual Studio [2], IBM's Eclipse [3]). Using IDE tools and other software packages it is fairly easy for programmers to expose application interfaces and/or consume existing interfaces leading to a gradual replacement of the current web server centric approaches (e.g. ASP, JSP, Servlets, CGI scripts) with WS centric approach.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it