MétaCan
Menu
Back to cohort
Record W2164092980 · doi:10.1002/ejic.200901262

Metallo‐Controlled Dynamic Molecular Tweezers: Design, Synthesis, and Self‐Assembly by Metal‐Ion Coordination

2010· article· en· W2164092980 on OpenAlex

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.

Bibliographic record

VenueEuropean Journal of Inorganic Chemistry · 2010
Typearticle
Languageen
FieldChemistry
TopicSupramolecular Chemistry and Complexes
Canadian institutionsQueen's University
Fundersnot available
KeywordsChemistryMolecular tweezersTweezersSupramolecular chemistryStackingSelf-assemblyCoordination complexMetal ions in aqueous solutionAllosteric regulationSubstrate (aquarium)Molecular recognitionMetalNanotechnologyCombinatorial chemistryMoleculeReceptorOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The introduction of controllable dynamic features into synthetic receptors represents a step towards “smart” adaptive nanodevices. We report herein our studies on the construction of dynamic molecular tweezers in which the binding of a substrate is allosterically controlled through shape switching of the receptor induced by metal‐ion coordination. 1D, 2D NMR spectroscopy and X‐ray crystallography were used to identify the nature of the metallosupramolecular entity generated. The presence of large aromatic naphthalene diimide moieties on the scaffold of the molecular tweezers strongly influences their coordination‐driven self‐assembly. It was found that these additional stacking interactions lead to the cooperative formation of a homocomplex, to the self‐sorted assembly of a hetero complex, and to the binding of non‐coordinating aromatic guests.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.196
Teacher spread0.191 · 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