Превентивная консервация как основа деятельности реставратора
Bibliographic record
Abstract
Публикация предлагает русский перевод главы «Основная деятельности реставратора» из книги одного из основателей реставрационной науки в Канаде и широко известного теоретика и практика реставрации Филипа Варда «The Nature of Conservation: Race against Time» (Природа консервации: гонка со временем», 1986), которая посвящена базовым основам профессии реставратора. Таковыми Ф. Вард видит меры превентивной консервации, формулирует основы данного вида реставрационной деятельности, в настоящее время получившего самую глубокую теоретическую проработку. Комментарии к переводу включают некоторые примеры практической реализации в рамках учебного процесса методик консервации-реставрации произведений живописи, основанных на идеях превентивной консервации. The publication presents a Russian translation of the chapter “The primary activities of conservator” from the book by one of the founders of restoration science in Canada, and the well-known theorist and practicing conservator Philip Ward “The Nature of Conservation: A Race Against Time”, devoted to the fundamentals of the profession of a conservator – to the preventive conservation measures. Philip Ward formulates the basic principles of this type of restoration activity, which has currently received deep theoretical elaboration. Comments on the translation include some cases of practical, applied implementation of conservation-restoration techniques of paintings within the educational process, based on the ideas of preventive 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 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".