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Metal‐Organic Frameworks: Polyrotaxane Frameworks

2014· other· en· W1485995731 on OpenAlexaff
Stephen J. Loeb, V. Nicholas Vukotic

Bibliographic record

VenueEncyclopedia of Inorganic and Bioinorganic Chemistry · 2014
Typeother
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRotaxaneNanotechnologyMetal-organic frameworkSolid-stateMaterials scienceOrganic moleculesMoleculeChemistryEngineeringSupramolecular chemistryEngineering physicsOrganic chemistryAdsorption

Abstract

fetched live from OpenAlex

Abstract This chapter describes recent progress in the design, preparation, and solid‐state structures of a sub‐class of metal‐organic frameworks (MOFs) in which the linking ligands are a type of mechanically interlocked molecule (MIM); a rotaxane. Incorporating rotaxane ligands into MOFs is of interest because of the possibility of demonstrating the dynamics of MIM systems in the solid‐state. The large amplitude molecular motions of MIMs are only just starting to be realized in the solid‐state. This chapter looks at the detailed development of these unique materials while offering some insight into the design process and future potential of these materials.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.1590.001

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 head0.210
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2014
Admission routes1
Has abstractyes

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