El proceso de informatización de los diccionarios valencianos anteriores al siglo XX: el Diccionario valenciano-castellano (1887) de Constantí Llombart
Bibliographic record
Abstract
In this article we describe the steps that were taken for the preparation of the Tresor lexicogràfic valencià (Valencian Lexicographical Thesaurus). This work aims to bring together all lexicographical data from the Valencian Dictionaries from the XVIth to the beginning of the XXth century. The first phase of this project has been completed and it includes all works between 1543 and 1880. In addition to the progressive incorporation of works to this first database, works that are still expected to be found among the collections of public or private libraries, this Thesaurus will include the two extensive Valencian collections of the XIXth century: Constantí Llombart (1887) and Martí i Gadea's work (1891). Due to the extensive content of these works, an individual and organized treatment of the information is necessary in order to proceed with their final inclusion. Recently, a research team of the Catalan Philology Department of the University of Alicante carried out the computerization of Llombart's Dictionary, and the team also expressed the wish to include their work in the other documents as well as submit Martí i Gadea's work to the same computerization process.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".