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Record W2127342232 · doi:10.1080/00032710903243570

Microsampling and Determination of Metals in Iron Gall Ink

2009· article· en· W2127342232 on OpenAlexaff
Kimberly Charleton, Alison E. Smith, Douglas M. Goltz

Bibliographic record

VenueAnalytical Letters · 2009
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsChemistryEnvironmental chemistryChromatographyMetallurgy

Abstract

fetched live from OpenAlex

Abstract Iron gall ink contains transition metals such as Fe, Cu, and Mn which are known to catalyze chemical reactions in support materials such as paper and parchment, which eventually leads to their deterioration over time. Identification of metals in ink can be an important step prior to the conservation treatment of a written document. In this work, syringe needles (16G–23G) were used to sample micro-cores (∼0.7 mm in diameter) of ink and paper prior to analysis. Metals were extracted from the micro-core with HNO3, prior to analysis using graphite furnace atomic absorption spectroscopy (GFAAS).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.532

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 head0.023
GPT teacher head0.298
Teacher spread0.276 · 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 designBench or experimental
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

Citations8
Published2009
Admission routes1
Has abstractyes

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