Guia temàtica Biblioteca ETSAB: Cornelia Hahn Oberlander (1921-2021)
Bibliographic record
Abstract
Bibliografia sobre Cornelia Hahn Oberlander: "Nascuda a Muelheim-Ruhr, Alemanya, va emigrar a Estats Units sent una nena. Va obtenir el diploma a Smith College el 1944 i va continuar els seus estudis a the Harvard Graduate School of Design on es va graduar el 1947. El 1953 Oberlander es va traslladar a Vancouver, British Columbia, amb el seu marit H. Peter Oberlander, arquitecte i urbanista. Cornelia va establir la seva pròpia firma de disseny i es va donar a conèixer pel seu treball col·laboratiu, socialment i mediambientalment responsable. Oberlander va ser anomenada membre de la Canadian Society of Landscape Architects (CSLA) i de l’American Society of Landscape Architects (ASLA). El 2013 va rebre la medalla ASLA, el més gran honor d’aquesta societat i al 2016 va rebre el més gran honor de la CSLA amb la medalla Governor General’s en Arquitectura del Paisatge." [Extret de: https://www.tclf.org/pioneer/cornelia-hahn-oberlander]
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.140 | 0.058 |
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".