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Record W2995140882 · doi:10.1039/c9sc05908c

Hydrophosphination of boron–boron multiple bonds

2019· article· en· W2995140882 on OpenAlexfundno aff
Tom E. Stennett, Arumugam Jayaraman, Tobias Brückner, Lea Schneider, Holger Braunschweig

Bibliographic record

VenueChemical Science · 2019
Typearticle
Languageen
FieldChemistry
TopicOrganoboron and organosilicon chemistry
Canadian institutionsnot available
FundersH2020 European Research CouncilEuropean CommissionNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsBoronDiphenylphosphineChemistryDouble bondOrganic chemistryPhosphineCatalysis

Abstract

fetched live from OpenAlex

Five compounds containing boron-boron multiple bonds are shown to undergo hydrophosphination reactions with diphenylphosphine in the absence of a catalyst. With diborenes, the products obtained are highly dependent on the substitution pattern at the boron atoms, with both 1,1- and 1,2-hydrophosphinations observed. With a symmetrical diboryne, 1,2-hydrophosphination yields a hydro(phosphino)diborene. The different mechanistic pathways for the hydrophosphination of diborenes are rationalised with the aid of density functional theory calculations.

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 score0.024
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.219
Teacher spread0.214 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

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