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Record W2976342189 · doi:10.1039/c9fd00083f

Physical insights into mechanistic processes in organometallic chemistry: an introduction

2019· article· en· W2976342189 on OpenAlexafffund
Robert H. Morris

Bibliographic record

VenueFaraday Discussions · 2019
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of TorontoToronto Public Health
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftCompute Canada
KeywordsChemistryOrganometallic chemistryNanotechnologyOrganic chemistryMaterials scienceCatalysis

Abstract

fetched live from OpenAlex

The challenges of research into the mechanisms of 4d versus 3d late transition metal homogeneous catalysts is considered here, particularly catalysts containing hydrides. Included are case studies of C-H bond activation as studied in a collaboration of the Weller and McIndoe groups where a ruthenium (4d) hydride intermediate is detected using ESI-MS analysis of the catalytic mixture, and as studied in a collaboration of the Thomas and Neidig groups where a hydride transfer step involving low valent iron (3d) catalytic species is investigated using low temperature methods including Mössbauer spectroscopy. In the asymmetric hydrogenation of olefins, mechanisms are considered for rhodium (4d) vs. the newly discovered cobalt (3d) metal catalysts from the Shevlin and Chirik groups. The Hintermair group has recently described a study of a Noyori ruthenium catalyst for the ATH of acetophenone in basic 2-PrOH using a variety of flow sampling methods including flow NMR. This mechanism is highlighted along with our iron hydride work in homogeneous asymmetric hydrogenation.

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 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 categoriesInsufficient 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 score0.095
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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 teacher head, not a consensus.

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

Citations4
Published2019
Admission routes2
Has abstractyes

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