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
Successful organizations increasingly rely on data analysis to develop new opportunities, guide business strategies and optimize resources. Online analytical processing (OLAP) systems are one of the most powerful technologies to provide the ability to interactively analyze multidimensional data from multiple perspectives. In this thesis we designed a new data structure, the PDCR-tree, that work on distributed systems providing low-latency transactions processing even for very complex queries. Using a PDCR-tree we demonstrate how to build a real-time OLAP system on a cloud based distributed platform called CR-OLAP. The CR-OLAP can be built using an m+1 machine scalable architecture so as the system load increases, the number of machines, m, can be increased to improve performance. Experiments show the system can process a query with 60% data coverage on a database with 80 million data tuples with a response time 0.3 seconds or less, well within the parameters of a real-time system.
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 | 0.000 | 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 | 0.002 |
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