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Record W2011556555 · doi:10.1039/b709061g

The use of aurophilic and other metal–metal interactions as crystal engineering design elements to increase structural dimensionality

2008· review· en· W2011556555 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

VenueChemical Society Reviews · 2008
Typereview
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSupramolecular chemistryToolboxCrystal engineeringCurse of dimensionalityNanotechnologyIntermolecular forceMaterials scienceChemistryComputer scienceCrystal structureMoleculeCrystallographyOrganic chemistryArtificial intelligence

Abstract

fetched live from OpenAlex

Research in the field of supramolecular chemistry has rapidly grown in recent years due to the generation of fascinating structural topologies and their associated physical properties. In order to rationally synthesize such high-dimensionality systems, several different classes of non-covalent intermolecular interactions in the crystal engineering toolbox can be utilized. Among these, attractive metallophilic interactions, such as those observed for d10 gold(I), have been increasingly harnessed as a design element to synthesize functional high-dimensional systems. This tutorial review will explore the methods by which gold(I) and other d10 and d8 metal centres have been employed to increase structural dimensionality via the formation of metal-metal interactions. Physical and optical properties associated with metallophilicity-based supramolecular structures will also be highlighted.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.096
GPT teacher head0.326
Teacher spread0.230 · 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