MétaCan
Menu
Back to cohort
Record W2016206795 · doi:10.1154/1.1431950

X-ray powder diffraction data for selected metal soaps

2002· article· en· W2016206795 on OpenAlexaff
Marie-Claude Corbeil, Laurianne Robinet

Bibliographic record

VenuePowder Diffraction · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsStearic acidZinc stearateStearateZincCopperMetalChemistryPalmitic acidOleic acidPowder diffractionFatty acidInorganic chemistryNuclear chemistryOrganic chemistryCrystallographyBiochemistry

Abstract

fetched live from OpenAlex

In order to better characterize metal soaps found in paint films or on metal surfaces, several metal soaps were synthesized and their X-ray powder diffraction patterns measured. Metal soaps were obtained from four different fatty acids found in drying oils, two saturated (palmitic and stearic acids) and two unsaturated (oleic and linoleic acids), and from copper, zinc, and lead, three metals that are typically found in metal alloys and paint systems. X-ray powder diffraction data are reported for the following compounds: palmitic acid, stearic acid, zinc palmitate, zinc stearate, zinc oleate, zinc linoleate, copper palmitate, copper stearate, copper oleate, lead palmitate, lead stearate, and lead oleate. Features that are characteristic of specific compounds were observed. Soaps obtained from different fatty acids with the same metal ion show differences, as do soaps obtained with the same fatty acid but with different metal ions. Differences were observed when X-ray powder diffraction data obtained for stearic acid and zinc stearate were compared to published data for these two compounds (PDF 38-1923 and 5-0079, respectively). In the case of stearic acid, differences could be explained by the fact that the specimen reported previously in PDF 38-1923 was likely contaminated with palmitic acid. In the case of zinc stearate, low angle data were missing from the original pattern PDF 5-0079 and peaks that were reported in other angular regions in fact consisted in more peaks that were not resolved due to broadening.

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)0.000
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: Dataset · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.092
GPT teacher head0.265
Teacher spread0.174 · 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
GenreDataset

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
Published2002
Admission routes1
Has abstractyes

Explore more

Same venuePowder DiffractionSame topicCultural Heritage Materials AnalysisFrench-language works237,207