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Record W2488075854 · doi:10.1002/aoc.3398

Immobilized copper(II) on nitrogen‐rich polymer‐entrapped Fe<sub>3</sub>O<sub>4</sub> nanoparticles: a highly loaded and magnetically recoverable catalyst for aqueous click chemistry

2015· article· en· W2488075854 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Organometallic Chemistry · 2015
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsAcadia University
Fundersnot available
KeywordsChemistryCatalysisCopperClick chemistryAlkyneAlkylAzideAqueous solutionPolymer chemistryBromideSodium azideArylNanoparticleMagnetic nanoparticlesHalideThermal stabilityInorganic chemistryNuclear chemistryOrganic chemistryChemical engineering

Abstract

fetched live from OpenAlex

A heterogeneous magnetic copper catalyst was prepared via anchoring of copper sulfate onto multi‐layered poly(2‐dimethylaminoethyl acrylamide)‐coated magnetic nanoparticles and was characterized using various techniques. The catalyst was found to be active, effective and selective for one‐pot three‐component reaction of alkyl halide, sodium azide and alkyne, known as copper‐catalyzed click synthesis of 1,2,3‐triazoles. As little as 0.3 mol% of catalyst was found to be effective under the optimum conditions. The catalyst could also be recycled and reused up to seven times without significant loss of activity. Thermal stability, high loading level of copper on catalyst, broad diversity of alkyl/benzyl/allyl bromide/chloride and alkyl/aryl terminal alkynes without isolation of azide intermediate, and good to excellent yields of products make this procedure highly economical. Copyright © 2015 John Wiley &amp; 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.

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 score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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