Library of Cationic Organic Dyes for Visible-Light-Driven Photoredox Transformations
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.
Bibliographic record
Abstract
Organic dyes can be excellent catalysts for photoredox chemistry, offering low price, low toxicity, and an exceptional range of available materials. Their use has been limited because in comparison to their transition-metal catalysts the spectroscopic, kinetic, and electrochemical information available is far more limited. To remediate this situation, we have determined the necessary data for 14 readily available dyes with excellent potential as photoredox catalysts. We have also demonstrated the utility of these dyes through visible-light-mediated reductive dehalogenation and Aza-Henry reactions. We envision that this collection of data will lead to an increase in the use of cationic dyes in photoredox processes because users will find the necessary information readily available.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it