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Record W2910203776 · doi:10.24264/lfj.18.4.6

Bindings of Rare Books from the Collections of the Romanian Academy Library - A Multidisciplinary Study

2018· article· en· W2910203776 on OpenAlexfundno aff
Cristina Carşote, Luminiţa Kövari, Carmen Cristina Albu, Emanuel Hadîmbu, Elena Badea, Lucreţia Miu, Gabriela Florenţa Dumitrescu

Bibliographic record

VenueLeather and Footwear Journal · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
FundersUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiCanada Excellence Research Chairs, Government of Canada
KeywordsRomanianMultidisciplinary approachLibrary sciencePolitical scienceComputer scienceLinguisticsPhilosophyLaw

Abstract

fetched live from OpenAlex

This paper presents an overview of the conservation state of the tawed white leather, parchment and reused parchment bookbindings from the Rare Book Collection of the Romanian Academy Library. The transdisciplinary study was jointly conducted by the researchers of INCDTP-ICPI and Manuscripts and Rare Book Department of the Romanian Academy Library. Over 50 bindings in alum-tawed (white) leather, parchment and reused parchment were analyzed in situ using specific non-invasive or micro-invasive analysis methods such as visual and microscopic analyses, thermal microscopy (imageMHT method), attenuated total reflection (ATR), Fourier transform infrared spectroscopy (FTIR), and X-ray Fluorescence Spectrometry (XRF). Based on these results, conservation sheets have been drawn up including damage status, threats and conservation recommendations for each investigated bookbinding. Two conservation sheets are illustrated for alum-tawed and re-used parchment bindings. This is the first Romanian study dedicated both to the artistic and material aspects of rare book bindings so far.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.030
GPT teacher head0.258
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2018
Admission routes1
Has abstractyes

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