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A preliminary study of the degradation of cyanoacrylate adhesives in the presence and absence of fossil material

2006· article· en· W2115526355 on OpenAlexaff
Jane L. Down, E. Kamińska

Bibliographic record

VenueJournal of Vertebrate Paleontology · 2006
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsCanadiana.org
Fundersnot available
KeywordsDegradation (telecommunications)AdhesiveMethacrylateChemistryFormaldehydeCyanoacrylateHydrolysisPolymerizationMoistureChemical engineeringEnvironmental chemistryPolymer chemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

ABSTRACT Fossils are frequently conserved with cyanoacrylate (CA) adhesives, which have never been scientifically assessed for their long-term stability and suitability for this application. The degradation of three types of CA adhesives were studied: an ethyl CA, an ethyl CA with added poly(methyl methacrylate) (PMMA), and a butyl CA, in the presence and absence of five different fossils obtained from various sites. The fossils were characterized by pH, moisture content, porosity, and ash content, as well as by their mineral and elemental composition. Hydrolytic degradation of polymerized CA adhesives was monitored by quantitative determination of formaldehyde, one of the degradation products. Both in the presence and absence of a fossil, butyl CA degraded more slowly than ethyl CA, making it attractive for fossil applications. It was also found that acidic fossil inhibits the degradation of CA adhesives, while neutral or alkaline fossils increase the CA degradation. The CA degradation appears to be correlated to some degree with a fossil's physical and chemical properties, but this requires further study. Further study is also necessary to determine how the observed CA degradation affects the actual fossil/CA bond strength.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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 teacher head, 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

Citations11
Published2006
Admission routes1
Has abstractyes

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