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Record W2799673741 · doi:10.2116/bunsekikagaku.67.195

<sup>13</sup>C-NMR Measurement of Pyrroloquinoline Quinone in Deuterium Oxide Using Cryo-probe and Spectral Identification by the Quantum Chemical Calculation

2018· article· en· W2799673741 on OpenAlexaff
Kazuto Ikemoto, Yuki Sakamoto, Kumiko Horiguchi, Shinichiro Nakamura

Bibliographic record

VenueBUNSEKI KAGAKU · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsDeuteriumMoietyChemistryQuinonePyrroloquinoline quinoneCarbon-13 NMRMoleculeDeuterium NMRAnalytical Chemistry (journal)Physical chemistryCofactorStereochemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Coenzyme pyrroloquinoline quinone (PQQ) is an important molecule in biology, chemistry and engineering. It has 14 kinds of carbon atoms, and there are 14 peaks in DMSO-d6 on the 13C-NMR measurement. The disodium salt of PQQ (Na2PQQ), used as food, is not dissolved in DMSO. A 13C-NMR assignment of Na2PQQ in deuterium oxide has not been reported. As for the measurement with a high sensitivity detector (cryo detector), 28 peaks could be observed in deuterium oxide. A quantum chemical calculation revealed that it has two states in equilibrium with the acetal structure by the addition of water to the quinone moiety.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.236
Teacher spread0.220 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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