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Record W2048288133 · doi:10.1021/jo1008383

Phospha-Münchnones: Electronic Structures and 1,3-Dipolar Cycloadditions

2010· article· en· W2048288133 on OpenAlexaff
Daniel J. St‐Cyr, Marie S. T. Morin, F. Bélanger-Gariépy, Bruce A. Arndtsen, Elizabeth H. Krenske, K. N. Houk

Bibliographic record

VenueThe Journal of Organic Chemistry · 2010
Typearticle
Languageen
FieldChemistry
TopicSynthesis and characterization of novel inorganic/organometallic compounds
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsDipolePhysicsCrystallographyChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

The reaction of imines, acid chlorides, PR(3), and base generates a new class of 1,3-dipoles: phospha-Munchnones. These 1,3-dipoles can undergo cycloadditions with alkynes followed by loss of phosphine oxides to form pyrroles. Cycloaddition reactivity is dependent upon the PR(3) employed, with PhP(catechyl) (catechyl = o-O(2)C(6)H(4)) providing the most rapid cycloadditions and optimal pyrrole yields. (1)H, (13)C, and (31)P NMR analysis and computations indicate that electron-poor catechyl-substituted phosphonites and phosphites favor a cyclic 1,3-dipolar structure, while more electron-rich phosphines instead favor the valence tautomeric acyclic ylides. X-ray crystallographic studies confirm this. Density functional theory calculations support the wide variety of P-O interactions induced by different PR(3) groups and indicate that the most efficient concerted 1,3-dipolar cycloadditions are those for dipoles whose ground-state geometry is most like the transition-state geometry. Reactions of these dipoles with monosubstituted alkynes bearing an electron-withdrawing group are calculated to occur by stepwise mechanisms. The presence of the phosphorus unit creates a large electronic bias across the 1,3-dipole, allowing for regioselective cycloadditions with substituted alkynes.

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 score0.034
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0340.000

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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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

Citations44
Published2010
Admission routes1
Has abstractyes

Explore more

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