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Record W2037796962 · doi:10.1039/c4cy01227e

Catalytic hydrogenation of functionalized amides under basic and neutral conditions

2014· article· en· W2037796962 on OpenAlexafffund
Jeremy M. John, Loorthuraja Rasu, Evan R. Antoniuk, Steven H. Bergens

Bibliographic record

VenueCatalysis Science & Technology · 2014
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsCatalysisChemistryCombinatorial chemistryOrganic chemistry

Abstract

A new, base-free high turnover number (TON) catalyst for hydrogenation of simple and functionalized amides is prepared by reacting [Ru(η<sup>3</sup>-C<sub>3</sub>H<sub>5</sub>)(Ph<sub>2</sub>P(CH<sub>2</sub>)<sub>2</sub>NH<sub>2</sub>)<sub>2</sub>]BF<sub>4</sub> and BH<sub>4</sub><sup>−</sup> under hydrogen.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Catalytic hydrogenation chemistry; a synthetic chemistry question.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

This studies a chemical catalyst and hydrogenation reaction, not research practice.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Domain chemistry paper on amide hydrogenation catalysis; object is chemical reactivity, not research practice.

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 score0.001
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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

Citations50
Published2014
Admission routes2
Has abstractyes

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