Análise do padrão brasileiro de metadados de teses e\ndissertações segundo o modelo entidade-relacionamento
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 the last decades, with the automation of the information systems and with the advent of digital libraries, norms, standards and techniques of the librarianship have been widely argued, analyzed, reevaluated and reorganized. Among these document organizing instruments there are rules and standards destined to the descriptive representation, like the\nMachine Readable Cataloguing Format, MARC, the Anglo-American Cataloguin Rules, AACR and the International Standard Bibliographic Descriptions, ISBD, that actually has been material for theoretical studies having as aim the development of the metadata standards for treatment of information for digital libraries. The objective of that thesis went analyze the pattern metadata Brazilian for Theses and Dissertations, MTD-BR, used in the project of the Digital Library of Theses and Dissertations, sponsored and directed by the Brazilian Institute of Scientific and Technological Information, IBICT, using the methodology of data modeling, in agreement with the Functional Demands for Bibliographical Description, FRBR, proposed by a specific group of studies of the International Federation of the Associations of Libraries, IFLA, based on the model entity-relationship, MER. Initially this methodology was applied\nISBD(G) and the results were presented in the final report of FRBR. Of this work, the same methodology went to base of two studies accomplished by Tom Delsey, of the National Library of Canada, being applied MARC and AACR. In to present thesis, the application of\nthis methodology of data modeling to the pattern of MTD-BR, will be the first initiative in Brazil of application of the methodology of FRBR. This study, presents the potentialities of the data modeling in the construction of libraries that digital. According to this research results, it is possible also to identify some points to be reflected in the development of a new\nversion of the MTD-BR standard, beyond proposals of magnifying of the metadata elements of this standard. Therefore, it was been evidenced to be essential that new studies must be carried out, using the application of this methodology to the other metadata standards, even though analising others tools of data modeling as the one intitled oriented object model, largelly applied for the information system project, considering its interface with librarianship norms, principles and instruments. It would be expected that not only the descriptive representation could be improve with this kind of studies, but also the area of thematic representation.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.002 | 0.001 |
| 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 it