Varia garcilasiana: un documento inédito. Los Zúñiga, otros parientes y un detalle de su casa natal
Bibliographic record
Abstract
n this article we first publish an unkown document by Elena de Zúñiga and her husband Garcilaso. Then —and it is the main part of this paper—, we study the most direct relatives of poet ́s wife, Elena de Zúñiga, people who became relatives of Garcilaso when he married Elena and who have received little attention.On the other hand, we also include the names of other nephews of the lyric poet and we clarify a detail about the main entrance of Lasos ́s palace where Garcilaso was almost certainly born.; Publicamos en este artículo un documento desconocido de D.ª Elena de Zúñiga y de su marido Garcilaso.Estudiamos después —y es el grueso de este estudio— a los familiares más directos de la esposa del poeta, personajes que se convirtieron en deudos del toledano a raíz de su matrimonio y a los que apenas se les ha prestado atención. Incluimos también los nombres de otros sobrinos carnales del lírico y aclaramos un de- talle respecto a la entrada principal de la casa de los Laso de la Vega en Toledo, edificio donde es casi seguro que nació Garcilaso.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".