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Record W2115415013 · doi:10.1002/anie.200301727

Two Birds with One Metallic Stone: Single‐Pot Catalysis of Fundamentally Different Transformations

2004· article· en· W2115415013 on OpenAlexaff
Alain Ajamian, James L. Gleason

Bibliographic record

VenueAngewandte Chemie International Edition · 2004
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsCatalysisCarbon fibersHeteroatomScope (computer science)Transformation (genetics)NanotechnologyChemistryMaterials scienceCombinatorial chemistryOrganic chemistryComputer scienceRing (chemistry)

Abstract

fetched live from OpenAlex

Advances in metal catalysis have revolutionized organic synthesis, with the scope of metal-catalyzed reactions now covering nearly all areas of carbon-carbon, carbon-hydrogen, and carbon-heteroatom bond formation. For years, the goal was to develop catalysts that were highly selective for a single transformation. However, a promising current area of research is the use of a single catalyst to mediate more than one transformation in a selective manner. Whereas much early work was focused on using a catalyst for several similar transformations, recent investigations have shown that it is also possible to employ a single catalyst for several very different transformations in a single reaction sequence. This Minireview focuses on methods in which the mechanisms of the transformations are fundamentally very different.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.016
GPT teacher head0.245
Teacher spread0.228 · 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

Citations361
Published2004
Admission routes1
Has abstractyes

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