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Record W4313907295 · doi:10.1515/pac-2022-1003

<i>HOME-Chemistry</i>: hydrazone as organo-metallic equivalent

2023· article· en· W4313907295 on OpenAlex
Chao‐Jun Li

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePure and Applied Chemistry · 2023
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersKillam TrustsFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsChemistryHydrazoneMetalOrganic chemistryComputational chemistry

Abstract

fetched live from OpenAlex

Abstract The modern synthetic chemistry heavily relies on the use of stoichiometric organometallic reagents to react with various electrophiles. The dependence on stoichiometric quantities of metals and often organic halides as precursors, in turn both produces copious amounts of metal halide wastes as well as leads to concerns on future metal sustainability. Inspired by the classical Wolff-Kishner reduction, our lab has recently developed a general strategy of HOME-Chemistry , directly using naturally abundant alcohols/aldehydes and ketones as feedstocks with the releasing of innocuous water and nitrogen gas. These reactions include 1,2-carbonyl/imine addition, conjugate addition, carboxylation, olefination, cross-coupling arylation/allylation, alkylation, hydroalkylation and C-heteroatom formations. This article provides a brief summary on this chemistry.

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), 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 score0.225
Threshold uncertainty score1.000

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)0.0070.001

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 head0.008
GPT teacher head0.219
Teacher spread0.210 · 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