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Record W1976256346 · doi:10.1021/jf101258x

Chemical Structure and Heterogeneity Differences of Two Lignins from Loblolly Pine As Investigated by Advanced Solid-State NMR Spectroscopy

2010· article· en· W1976256346 on OpenAlexaff
Kevin M. Holtman, Na Chen, Mark A. Chappell, John F. Kadla, Ling Xu, Jingdong Mao

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLigninHeteronuclear moleculeCelluloseChemistryChemical shiftSpin diffusionNuclear magnetic resonance spectroscopyCarbon-13 NMRChemical structureSolid-state nuclear magnetic resonanceExtraction (chemistry)Chemical compositionDiffusionAnalytical Chemistry (journal)Organic chemistryNuclear magnetic resonancePhysical chemistry

Abstract

fetched live from OpenAlex

Advanced solid-state NMR was employed to investigate differences in chemical structure and heterogeneity between milled wood lignin (MWL) and residual enzyme lignin (REL). Wiley and conventional milled woods were also studied. The advanced NMR techniques included 13C quantitative direct polarization, various spectral-editing techniques, and two-dimensional 1H-13C heteronuclear correlation NMR with 1H spin diffusion. The 13C chemical shift regions between 110 and 160 ppm of two lignins were quite similar to those of two milled woods. REL contained much more residual carbohydrates than MWL, showing that MWL extraction more successfully separated lignin from cellulose and hemicelluloses than REL extraction; REL was also of higher COO, aromatic C-C, and condensed aromatics but of lower aromatic C-H. At a spin diffusion time of 0.55 ms, the magnetization was equilibrated through the whole structure of MWL lignin, but not through that of REL, indicating that REL is more heterogeneous than MWL.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.006
GPT teacher head0.245
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

Citations39
Published2010
Admission routes1
Has abstractyes

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