Aluminum: History, Technology, and Conservation
Bibliographic record
Abstract
The current volume brings together papers presented at the 2014 “Aluminum: History, Technology and Conservation” conference held at the Smithsonian Institution’s American Art Museum; the conference was followed by a hands-on workshop held at the National Air and Space Museum’s Steven F. Udvar-Hazy Center, which utilized the museum’s collections to illustrate aluminum’s use, conservation challenges, and repair techniques as well as to introduce participants to analytical techniques such as X-ray fluorescence for the identification of aluminum alloys and finishes. The three day international conference and two-day workshop were co-hosted with the Smithsonian Institution, the Foundation for the American Institute for Conservation and the International Council of Museums Committee for Conservation Metals Working Group. An unprecedented group of speakers, organizers, and sponsors made possible the first ever conservation conference solely dedicated to aluminum. The conference featured presentations by twenty-seven speakers from Europe, Asia, Australia, and North America who explored various aspects of degradation phenomena and conservation strategies for aluminum objects, from sculpture to aircraft, from nineteenth-century jewelry to underwater archaeological objects. The proceedings are divided into eight categories and represent the various themed sessions: the history and manufacturing of aluminum, corrosion and deterioration, characterization and identification, conservation of archaeological objects, conservation and use in contemporary art, conservation of architectural elements, surface treatments and inhibition, and preventative conservation.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".