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
We provide a principled extension of SQL, called SchemaSQL , that offers the capability of uniform manipulation of data and schema in relational multidatabase systems. We develop a precise syntax and semantics of SchemaSQL in a manner that extends traditional SQL syntax and semantics, and demonstrate the following. (1) SchemaSQL retains the flavor of SQL while supporting querying of both data and schema. (2) It can be used to transform data in a database in a structure substantially different from original database, in which data and schema may be interchanged. (3) It also permits the creation of views whose schema is dynamically dependent on the contents of the input instance. (4) While aggregation in SQL is restricted to values occurring in one column at a time, SchemaSQL permits "horizontal" aggregation and even aggregation over more general "blocks" of information. (5) SchemaSQL provides a useful facility for interoperability and data/schema manipulation in relational multidatabase systems. We provide many examples to illustrate our claims. We clearly spell out the formal semantics of SchemaSQL that accounts for all these features. We describe an architecture for the implementation of SchemaSQL and develop implementation algorithms based on available database technology that allows for powerful integration of SQL based relational DBMS. We also discuss the applicability of SchemaSQL for handling semantic heterogeneity arising in a multidatabase 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 | 0.001 |
| 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 | 0.001 |
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