Documentation for emergency condition mapping of Decorated historic surfaces at the Caid Residence, the Kasbah of Taourirt (Ouarzazate, Morocco)
Bibliographic record
Abstract
Abstract. As it is broadly understood, recording serves as a basis for the diagnosis, treatment and preservation of historic places and contributes to record our built cultural heritage for posterity. This work is not a stand-alone practice but a part of the overall conservation process of cultural heritage at imminent risk of irreversible damage. Recording of heritage places should be directly related to the needs, skills and the technology that are available to the end users that are responsible for the management and care of these sites. They should be selected in a way that the future managers of these sites can also access and use the data collected. This paper explains an innovative heritage recording approach applied by the Getty Conservation Institute (GCI) and Carleton Immersive Media Studio (CIMS) in the documentation of historic decorated surfaces at the Caïd Residence, located at Tighermt (Kasbah) Taourirt in Ouarzazate, Morocco; as part of a collaborative project between the GCI and the Centre de Conservation et Réhabilitation du Patrimoine Architectural des Zones Atlasiques et Sub-Atlasiques (CERKAS) to rehabilitate the entire architectural ensemble. The selected recording techniques were used for the rapid mapping of conditions of the decorated surfaces at the Caïd Residence using international standards. The resulting work is being used by GCI staff, consultants and CERKAS team to conduct emergency stabilization and protection measures for these important decorated surfaces.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".