Structural Repairs of Multidimensional Databases.
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
Abstract. In a multidimensional (MD) database, dimensions may be subject to semantic conditions that are not enforced by MD DBMSs or data warehouse applications. Strictness and homogeneity are possibly two of them; and are crucial for the efficiency and correctness of answering MD aggregate queries and updating materialized aggregate views. Dimensions may become inconsistent, i.e. non-strict or heterogeneous, as the result of update operations. As a methodology to restore consistency, we propose and investigate changes to the dimension schema, as an alternative to changes on the dimension instance. We introduce the notion of minimal structural repair, and establish that under certain conditions, a structural repair reduces the cost wrt changing the dimension instance. We also show that it allows for a correct rewriting of queries posed to the original MD model into queries in terms of the new schema. Finally, we show how query-scoped calculated members in MDX can be used to create virtual repairs that simulate structural repairs. 1
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 | 0.000 | 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