Peptide Electron Transfer: More Questions than Answers
Bibliographic record
Abstract
Nature has specifically designed proteins, as opposed to DNA, for electron transfer. There is no doubt about the electron transfer within proteins compared with the uncertain and continuing debate about charge transfer through DNA. However, the exact mechanism of electron transfer within peptide systems has been a source of controversy. Two different mechanisms for electron transfer between a donor and an acceptor, electron hopping and bridge-assisted superexchange, have been proposed, and are supported by experimental evidence and theoretical calculations. Several factors were found to affect the kinetics of this process, including peptide chain length, secondary structure and hydrogen bonding. Electrochemical measurements of surface-supported peptides have contributed significantly to the debate. Here we summarize the current approaches to the study of electron transfer in peptides with a focus on surface measurements and comment on these results in light of the current and often controversial debate on electron transfer mechanisms in peptides.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.004 | 0.032 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".