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
The buffer pool in a DBMS is used to cache the disk pages of the database. Because typical database workloads are I/O-bound, the effectiveness of the buffer pool management algorithm is a crucial factor in the performance of the DBMS. In IBM's DB2 buffer pool, the page cleaning algorithm is used to write changed pages to disks before they are selected for replacement. We conducted a detailed study of page cleaning in DB2 version 7.1.0 for Windows by both trace-driven simulation and measurements. Our results show that system throughput can be increased by 19% when the page cleaning algorithm is carefully tuned. In practice, however the manual tuning of this algorithm is difficult. A self-tuning algorithm for page cleaning is proposed posed in this paper to automate this tuning task. Simulation results show that the self-tuning algorithm can achieve performance comparable to the best manually tuned 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 | 0.001 |
| 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