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Record W2165489503 · doi:10.1039/b918402c

DFT studies of the degradation mechanism of methyl mercury activated by a sulfur-rich ligand

2010· article· en· W2165489503 on OpenAlexfundno aff
Xichen Li, Rong‐Zhen Liao, Wenchang Zhou, Guangju Chen

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMercury (programming language)SulfurDegradation (telecommunications)ChemistryLigand (biochemistry)Environmental chemistryOrganic chemistryComputer scienceBiochemistryReceptor

Abstract

fetched live from OpenAlex

We describe theoretical insights into the mechanism of Hg-C bond protonolysis in methyl mercury coordinated by the tris(2-mercapto-1-tert-butylimidazolyl)hydroborato ligand, the structural and functional analogue of the organomercurial lyase MerB. Different cleavage pathways including both frontside and backside attack transition states were systematically studied by the hybrid density functional method B3LYP. Dependence of Hg-C bond activation on the primary sulfur coordination number of mercury was elaborated, and conceptual DFT indexes were suggested to be more appropriate than gross charge of atom sites in interpreting the dependence. Furthermore, absence of configurational inversion in MerB-catalyzed reactions was accounted for by examinations of the backside protonolysis pathways in the present system. Lastly, a rationalization was provided about the choice between different characteristics of transition states including both four-center and six-center ones.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.273
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations18
Published2010
Admission routes1
Has abstractyes

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