XML Schema Integration and E-Commerce
Bibliographic record
Abstract
XML (eXtensible Markup Language) is used to describe semi-structured data, i.e., irregular or incomplete data whose structure may be subject to unpredictable changes. Unlike traditional semi-structured data, XML documents are self-describing, thus XML provides a platform-independent means to describe data and, therefore, can transport data from one platform to another (Bray, Paoli, & Sperberg-McQueen, 1998). XML documents can be both created and used by applications. The valid content, allowed structure, and metadata properties of XML documents are described by their related schema(s) (Thompson, Beech, Maloney, & Mendelsohn, 2001). An XML document is said to be valid if it conforms to its related schema. A schema also gives additional semantic meaning to the data it is used to tag. The schema is provided independently of the data it describes. Any given data set may rely on multiple schemas for validation. Any given schema may itself refer to multiple schemas.
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) | 0.001 | 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 | 0.001 |
| 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 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".