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Record W2035797219 · doi:10.1021/jo0524932

<sup>15</sup>N NMR Chemical Shifts for the Identification of Dipyrrolic Structures

2006· article· en· W2035797219 on OpenAlexaff
Tabitha E. Wood, Bob Berno, Cory S. Beshara, Alison Thompson

Bibliographic record

VenueThe Journal of Organic Chemistry · 2006
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsMcMaster UniversityDalhousie University
Fundersnot available
KeywordsChemistryChemical shiftIdentification (biology)Nuclear magnetic resonance spectroscopyComputational chemistryStereochemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A variety of dipyrromethanes and dipyrromethenes have been prepared, and their 15N NMR chemical shifts have been measured by two-dimensional correlation to 1H NMR signals. The nitrogen atoms in five examples of dipyrromethanes consistently exhibit chemical shifts around -231 ppm, relative to nitromethane. Seven examples of hydrobromide salts of meso-unsubstituted dipyrromethenes consistently display 15N chemical shifts around -210 ppm, while their corresponding zinc(II) complexes exhibit chemical shifts around -170 ppm. The presence of electron-withdrawing substituents on one of the pyrrolic rings of dipyrromethenes affects the chemical shifts of both of the nitrogen nuclei in the molecule. Boron difluoride complexes of meso-unsubstituted dipyrromethenes display 15N chemical shifts around -190 ppm. Two examples of free-base dipyrromethenes bearing substituents at the meso-position exhibit 15N chemical shifts at approximately -156 ppm, and for the zinc complexes of these compounds at -162 ppm. One-bond nitrogen-hydrogen coupling constants, when measurable, were consistently in the range of -96 Hz. Since the measured 15N chemical shifts have such a high regularity correlated to structure, they can be used as diagnostic indications for identifying the structure of dipyrrolic compounds.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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
Published2006
Admission routes1
Has abstractyes

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