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Record W2016126351 · doi:10.1021/jf062199q

Differences between Lignin in Unprocessed Wood, Milled Wood, Mutant Wood, and Extracted Lignin Detected by <sup>13</sup>C Solid-State NMR

2006· article· en· W2016126351 on OpenAlexaff
Jingdong Mao, Kevin M. Holtman, Jay T. Scott, John F. Kadla, Klaus Schmidt‐Rohr

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2006
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLigninChemistryAldehydeCarbon-13 NMRNuclear magnetic resonance spectroscopyOrganic chemistrySolid-state nuclear magnetic resonanceExtraction (chemistry)Nuclear chemistryNuclear magnetic resonanceCatalysis

Abstract

fetched live from OpenAlex

Solid-state 13C nuclear magnetic resonance (NMR) spectroscopy was applied to intact and isolated loblolly pine wood samples to identify potential structural changes induced by tree age, milling, lignin extraction, or naturally occurring mutations. Special attention was paid to ketone and aldehyde as well as nonpolar alkyl groups, which could be observed at low concentrations (<2 in 1000 C) using improved spinning-sideband suppression with gated decoupling. Carbonyl structures were present in intact wood, and there are more keto groups than aldehydes. Their concentrations increased from juvenile to mature wood and with milling time, whereas extraction did not alter the C=O fraction. Significant amounts of aldehyde and dihydroconiferyl alcohol residues were present in coniferyl aldehyde dehydrogenase-deficient wood, confirming solution-state NMR spectra of the corresponding lignin. These results demonstrate the utility of solid-state NMR as an assay for changes in the lignin structure of genetically modified plants.

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 categoriesMeta-epidemiology (narrow)
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 score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.179
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 teacher head, not a consensus.

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

Citations70
Published2006
Admission routes1
Has abstractyes

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