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Record W3138350370 · doi:10.1002/chem.202181663

Frontispiece: Enhancing Magnetic Communication between Metal Centres: The Role of <i>s</i>‐Tetrazine Based Radicals as Ligands

2021· paratext· en· W3138350370 on OpenAlexaff
Niki Mavragani, Alexandros A. Kitos, Jaclyn L. Brusso, Muralee Murugesu

Bibliographic record

VenueChemistry - A European Journal · 2021
Typeparatext
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTetrazineDelocalized electronNanotechnologyChemistryRadicalCombinatorial chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

s-Tetrazine is a six-membered aromatic nitrogen-rich compound that can be easily reduced to form a radical anion with highly delocalized electron density. Additionally, it offers limitless possibilities for creating novel materials owing to the possible derivatization at 3- and 6-positions and its highly tunable nature. In recent years, this versatility has led to the emergence of a wide variety of materials based on s-tetrazines, ranging from energetic materials to magnetic/conducting systems. While examples of radical bridged coordination compounds with specific tetrazines have begun to emerge, there are still a large number of tetrazinyl derivatives that remain unexplored. With the increased research interest and efforts placed on developing tetrazine-based materials, the pathway is now open for innovative exploration where magnetic communication through s-tetrazine plays a pivotal role. In their Minireview on page 5091, M. Murugesu et al. highlight the incorporation of tetrazines as tunable ligands in the development of novel high-performing molecule-based magnets.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0670.001

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 head0.010
GPT teacher head0.241
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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