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Record W1983831709 · doi:10.1002/jlcr.722

Efficient <i>in‐loop</i> synthesis of high specific radioactivity [<sup>11</sup>C]carfentanil

2003· article· en· W1983831709 on OpenAlexaff
Andrei R. Studenov, Salma Jivan, K. Buckley, Michael J. Adam

Bibliographic record

VenueJournal of Labelled Compounds and Radiopharmaceuticals · 2003
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicChemical Reactions and Isotopes
Canadian institutionsTRIUMF
FundersJohns Hopkins University
KeywordsChemistryYield (engineering)Methyl iodideAmmoniaNitrileChemical synthesisNuclear chemistryRadiochemistryMedicinal chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The synthesis of the precursor for [11C]carfentanil and the precursor labelling with 11C have both been improved. The problem ‘bottleneck’ step in the carfentanil precursor synthesis, due to low chemical yield (14%) of intermediates nitrile into amide conversion, has been solved. Application of a H2O2/K2CO3/DMSO reaction method significantly increased the yield of this chemical transformation (up to 84%). A simple and straight‐forward synthesis of [11C]carfentanil was achieved by combining in‐loop methylation of the ammonia salt of the precursor by [11C]CH3I, using tetrabutylammonium hydroxide as a base, with a previously developed product purification procedure using a C2 extraction disc. A decay corrected yield with respect to [11C]CH3I of [11C]carfentanil was 64±12% (n=6) with the synthesis time of 21 min. The radiochemical purity was >98%. Comparatively high specific radioactivity of [11C]carfentanil [11.2±4.8 Ci/μmol (EOS, n=5)] was partially attributed to the use of [11C]methane target gas for production of carbon‐11 methyl iodide. Copyright © 2003 John Wiley & Sons, Ltd.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.058
GPT teacher head0.367
Teacher spread0.309 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

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