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Record W2003351827 · doi:10.1515/hf.2005.019

Quantitative 1H NMR analysis of alkaline polysulfide solutions

2005· article· en· W2003351827 on OpenAlexafffund
Dimitris S. Argyropoulos, Yihua Hou, Ramana Ganesaratnam, David N. Harpp, Keiichi Koda

Bibliographic record

VenueHolzforschung · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pheromone Research and Control
Canadian institutionsMcGill University
FundersDivision of Graduate EducationNatural Sciences and Engineering Research Council of CanadaMcGill UniversityUniversity of Arizona
KeywordsPolysulfideChemistryReagentAqueous solutionQuantitative analysis (chemistry)Sodium hydroxideHydroxideInorganic chemistryOrganic chemistryChromatographyPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract A novel analytical protocol for the absolute determination of the various polysulfide species present in alkaline aqueous media was developed. The method is comprised of alkylating polysulfide ions with dimethyl sulfate, followed by quantitative proton NMR spectroscopy using 1,3,5-tributyl benzene as the internal standard. In order to arrive at a quantitative acquisition protocol, a number of variables were examined in detail for their effect on the alkylation reaction, including the presence of oxygen, the amount of dimethyl sulfate and sodium hydroxide, and the various modes of adding the alkylating reagent to the reaction mixture. Most of these variables were found to play a role in determining the quantitative reliability of the procedure. Consequently, a method is described that can be used for the efficient and reliable quantitative detection of polysulfide ions. The protocol developed could be particularly useful in promoting our understanding of the intricate and delicate chemistry of polysulfide equilibria in aqueous alkaline media.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.276
Teacher spread0.239 · 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 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

Citations23
Published2005
Admission routes2
Has abstractyes

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