Thesauri in the modern world: Research and prospects for application
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
In today’s information society, where the amount of available information is constantly growing, the issues of semantic classification and data organization are becoming more and more relevant. Efficient information retrieval and analysis play a key role in scientific and applied fields, requiring innovative tools for semantic processing of texts and words. The study aims to analyse the structure, role, and potential of thesauri by means of statistical and structural analysis methods, as well as analytical-synthetic and comparative methods. The results emphasized the importance of thesauri in providing accurate and structured access to information in various fields. Statistical results showed that the broadest thesaurus categories in Library of Congress Subject Headings (LCSH) were art, library systems, medicine, culture, and media, followed by scientific research, linguistics, and semantics. The study presented a hierarchy between the subject area of research, thesaurus categories, narrowly focused terms, and ways to improve the classification and presentation of information. For example, the subject area art and culture included such thesaurus categories as sculpture, literature, painting, at the same time, the category sculpture can include such terms as sculpture group, statue, bust. Among the prospects of thesaurus development, we suggest improvement of information classification quality, efficiency of data analysis, optimization of catalogue search, development of new thesaurus structures, identification of interrelations between terms by means of semantic analysis, improvement of information accessibility of materials in libraries. The practical significance of the research lies in providing a basis for the development of effective strategies for thesaurus tools application in information technology, medicine, education, and art.
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 | 0.003 | 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 | 0.003 |
| 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