Bibliographic record
Abstract
This volume contains an impressive number of essays by authors from diversebackgrounds. What the title does not indicate is the reason for this publication– the conference “Layers of Islamic Art and the Museum Context” (held inBerlin during January 13-16, 2010) in cooperation with the Aga Khan Trustfor Culture, the Museum of Islamic Art in Berlin, and the “Europe in the MiddleEast – The Middle East in Europe” (EUME). The EUME is a Berlin-basedresearch program initiated by the Brandenburg Academy of Science, the FritzThyssen Foundation, Wissenschaftskolleg zu Berlin, and the Forum TransregionaleStudien. This publication drew upon the expertise of the Aga KhanNetwork and experts in Germany because it was originally to be a workshopfocused on the reorganization of Berlin’s Museum of Islamic Art (MIA) aswell as a study for Toronto’s Museum of Islamic Art, which will open thisyear and house the Aga Khan’s personal collection.The forum offers a certain diversity of voices regarding issues in general(the display of Islamic art around the world) and specific to the MIA at thePergamon Museum. Its twenty-nine essays are divided into five sections: “In-132 The American Journal of Islamic Social Sciences 31:2troduction,” ...
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".