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Record W2055121733 · doi:10.1021/la025714x

A General Correlation for the <sup>129</sup>Xe NMR Chemical Shift−Pore Size Relationship in Porous Silica-Based Materials

2002· article· en· W2055121733 on OpenAlexaff
Victor V. Terskikh, Igor Moudrakovski, Steven R. Breeze, Stephen Lang, Christopher I. Ratcliffe, John A. Ripmeester, Abdelhamid Sayari

Bibliographic record

VenueLangmuir · 2002
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsSteacie Institute for Molecular SciencesUniversity of Ottawa
Fundersnot available
KeywordsPorosityPorous mediumMaterials scienceChemistryCharacterization (materials science)Analytical Chemistry (journal)MineralogyNanotechnologyChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

A general correlation for the 129 Xe NMR chemical shift−pore size relationship (δ versus D ) in porous silica-based materials over the range 0.5−40 nm has been demonstrated: δ = δ s /(1 + D / b ), with δ s = 116 ± 3 ppm and b = 117 ± 8 Å for the 34 materials studied. The correlation may be used in the characterization of silica samples with unknown pore structure. Even within this general correlation, subsets of materials of similar origin display finer correlations that indicate an acute sensitivity to details of the pore surfaces.

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)0.004
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.025
GPT teacher head0.274
Teacher spread0.249 · 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

Citations125
Published2002
Admission routes1
Has abstractyes

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