Bibliographic record
Abstract
With the rapid advance of the Internet, management of structured documents such as XML documents has become more and more important (Marchiori, 1998). As a simplified version of SGML, XML is recommended by W3C (World Wide Web Consortium, 1998a; World Wide Web Consortium, 1998b) as a document description meta-language to exchange and manipulate data and documents on the WWW. It has been used to code various types of data in a wide range of application domains, including a Chemical Markup Language for exchanging data about molecules, the Open Financial Exchange for swapping financial data between banks and banks and customers, as well as a Geographical Markup Language for searching geographical information (Bosak, 1997; Zhang & Gruenwald, 2001). Also, a growing number of legacy systems are adapted to output data in the form of XML documents.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.026 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".