Bibliographic record
Abstract
espanolGano en 1996 el “Leon de Oro” en Venecia.En 2014 le conceden la “Medaille de Vermeil et d’Honneur de l’Academie d’Architecture”.En 2015 crea su propia escuela de arte y arquitectura, Confluenc.En 2015 le otorgan el Doctorate Honoris Causa of Architecture - Laval University, Quebec.En 2016 fue galardonada con el premio Jane Drew.En 2018 fue designada Comandante de la Orden Nacional del Merito (Francia). EnglishIn 1996 she was awarded with el “Leone de Oro” in Venice.In 2014 she was awarded with la “Medaille de Vermeil et d’Honneur de l’Academie d’Architecture”.In 2015 she founded her own school of art and architecture Confluence Institute.In 2015 she was awarded with the Doctorate Honoris Causa of Architecture - Laval University, Quebec.In 2016 she was awarded with the Jane Drew prize.In 2018 she was appointed Commander of Ordre National du Merite (France).
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.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".