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Record W4312873568 · doi:10.15376/biores.12.2.hubbe

Deacidification of acidic books and paper by means of non-aqueous dispersions of alkaline particles: A review focusing on completeness of the reaction

2017· review· en· W4312873568 on OpenAlexaff
Martin A. Hubbe, Richard Smith, Xuejun Zou, Svetozár Katuščák, Antje Potthast, Kyujin Ahn

Bibliographic record

VenueBioResources · 2017
Typereview
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsFPInnovations
Fundersnot available
KeywordsAqueous solutionNeutralizationAlkaline hydrolysisHydrolysisCondensationChemistryChemical engineeringPolymer scienceMaterials scienceOrganic chemistryEngineeringMeteorologyPhysics

Abstract

fetched live from OpenAlex

Deacidification refers to chemical treatments meant to slow down the acid hydrolysis and embrittlement of books and paper documents that had been printed on acidic paper. From the early 1800s up to about 1990, papermakers used aluminum sulfate, an acidic compound, in most printing papers. Certain deacidification methods use non-aqueous media to distribute alkaline mineral particles such as MgO within the pages of the treated books. Evidence is considered here as to whether or not the proximity of alkaline particles within such documents is sufficient to neutralize the acidic species present. Because much evidence suggests incomplete neutralization, a second focus concerns what to do next in cases where books already have been treated with a non-aqueous dispersion system. Based on the literature, the neutralization of acidic species within such paper can be completed by partial moistening, by high humidity and pressure, by water condensation, as well as by optional treatments to enhance paper strength and a final drying step.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.126
GPT teacher head0.316
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2017
Admission routes1
Has abstractyes

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