Frontispiece: Enhancing Magnetic Communication between Metal Centres: The Role of <i>s</i>‐Tetrazine Based Radicals as Ligands
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.120 | 0.083 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".