Bibliographic record
Abstract
A client on a client-centric OLAP system is capable of performing OLAP operations on data downloaded from the OLAP server. A previous research study has shown that this concept can work very well for some common data visualization scenarios. As a proof-of-concept, a research prototype was built where the client was a web-browser on a desktop machine. In this research, our focus has shifted to mobile devices, such as a tablet, which is more resource-constrained. Our objective is to find out the pros and cons of a web-based client vis-à-vis an app-based client, i.e., one that runs on the native operating system. Two research prototypes have been built, one for each type of client, to run in a client-centric OLAP system. We compare their architectures, software implementation aspects and performance on `real life' data. We pay special attention on how software running on mobile devices handles unusually high volume of data. We also compare the performance of app-based clients running in a client-centric and a server-centric system respectively.
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.
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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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".