MétaCan
Menu
Back to cohort
Record W4409314864 · doi:10.1021/acs.inorgchem.5c00821

Probing the Reversible Binding of Anionic Reactive Sulfur and Nitrogen Species in Imidazolium Receptors with Directional C–H Hydrogen Bonds

2025· article· en· W4409314864 on OpenAlexaff
Amanda G. Davis, Lev N. Zakharov, Michael D. Pluth

Bibliographic record

VenueInorganic Chemistry · 2025
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsImpact
FundersDivision of Graduate EducationDivision of ChemistryNational Institute of General Medical Sciences
KeywordsChemistrySulfurHydrogen bondNitrogenReceptorHydrogenInorganic chemistryStereochemistryPolymer chemistryOrganic chemistryMoleculeBiochemistry

Abstract

fetched live from OpenAlex

H 2 S and NO are physiologically important signaling molecules with complex roles in biology and intermolecular crosstalk. Although these species are often referred to as neutral on paper, they are primarily found in anionic and/or oxidized forms in aerobic solutions as HS – or NO 2 – /NO 3 –, respectively. Despite the prominence of these anions in biology, particularly HS – and NO 2 –, few investigations have focused on the molecular recognition and reversible binding of these important species. Using a library of imidazolium receptors with C–H hydrogen bonding interactions, we investigate the influences on binding affinity through modulation of charge, multiplicity, and preorganization, while also investigating how anion volume impacts binding. These factors are probed by solution-state titration experiments and solid-state X-ray crystallographic data showing the specific molecular interactions involved in guest binding. Both solution-state NMR and solid-state X-ray crystallography support the importance and abundance of C–H···X – interactions in facilitating guest binding as well as conformational changes upon anion recognition.

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 categoriesnone
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 score0.012
Threshold uncertainty score0.504

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.194
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInorganic ChemistrySame topicMolecular Sensors and Ion DetectionFrench-language works237,207