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Record W2036135619 · doi:10.1002/marc.201300826

Sandwich Complex‐Containing Macromolecules: Property Tunability Through Versatile Synthesis

2014· review· en· W2036135619 on OpenAlexaff
Alaa S. Abd‐El‐Aziz, Christian Agatemor, Nola Etkin

Bibliographic record

VenueMacromolecular Rapid Communications · 2014
Typereview
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMacromoleculeMaterials scienceNanotechnologyBridging (networking)Chemical physicsChemistryComputer science

Abstract

fetched live from OpenAlex

Sandwich complexes feature unique properties as the physical and electronic properties of a hydrocarbon ligand or its derivative are integrated into the physical, electronic, magnetic, and optical properties of a metal. Incorporation of these complexes into macromolecules results in intriguing physical, electrical, and optical properties that were hitherto unknown in organic-based macromolecules. These properties are tunable through well-designed synthetic strategies. This review surveys many of the synthetic approaches that have resulted in tuning the properties of sandwich complex-containing macromolecules. While the past two decades have seen an ever-growing number of research publications in this field, gaps remain to be filled. Thus, we expect this review to stimulate research interest towards bridging these gaps, which include the insolubility of some of these macromolecules as well as expanding the scope of the sandwich complexes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.092
GPT teacher head0.344
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations82
Published2014
Admission routes1
Has abstractyes

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