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Record W3037455148 · doi:10.1002/aoc.5838

Manganese oxide nanoparticles supported on graphene oxide as an efficient nanocatalyst for the synthesis of 1,2,4‐oxadiazoles from aldehydes

2020· article· en· W3037455148 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 · 2020
Typearticle
Languageen
FieldChemistry
TopicSynthesis and Biological Evaluation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryCatalysisManganeseNanocompositeGrapheneOxideNanoparticleManganese oxideOrganic chemistryInorganic chemistryCombinatorial chemistryChemical engineering

Abstract

fetched live from OpenAlex

The easy synthesis of graphene oxide (GO)‐supported manganese dioxide (MnO 2 ) nanoparticles as a stable heterogeneous nanocatalyst (MnO 2 @GO) is described. This catalyst was investigated in the synthesis of 1,2,4‐oxadiazoles from amidoximes and aldehydes via a cyclization and oxidation process. The nanocomposite was prepared and characterized using various techniques. The catalytic application of the nanocomposite was examined in the reaction of a variety of aldehydes with aliphatic and aromatic amidoximes. The stable and robust catalyst was recycled for seven consecutive runs without a significant decrease in the catalytic activity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.026
GPT teacher head0.238
Teacher spread0.212 · 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