Análisis de la traducción automática inglés-español de las unidades terminológicas nominales univerbales del subcampo de especialidad del fútbol: el caso de ball, shot y referee
Bibliographic record
Abstract
El lenguaje de especialidad del fútbol y la traducción automática constituyen dos objetos de estudio trascendentes en el ámbito de la investigación académica de los Estudios de Traducción y de la Lingüística Contrastiva, pero todavía no se han abordado de manera conjunta. Estos dos marcos de investigación convergen en el presente trabajo fin de máster, que persigue el objetivo de comprobar si la traducción automática del inglés al español de las unidades terminológicas nominales univerbales del subcampo de especialidad del fútbol es adecuada. Para lograr este objetivo, se emplea una metodología basada en corpus para analizar la traducción al español de unidades terminológicas en inglés extraídas de crónicas futbolísticas en directo.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".