Effect of External Electric Field Upon Selected Proteogenic Amino Acids
Bibliographic record
Abstract
Effect of external electric field (EEF) of 0.001, 0.005 and 0.01 a.u. upon molecular energy, charge distribution and dipole moments of non-dissociated and inner salt forms of alanine (Ala), arginine (Arg), aspartic acid Asp), cysteine (Cys), glutamic acid (Gln), glycine (Gly), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), ornithine (Orn), proline (Pro), serine (Ser), threonine (Thr), tryptophan (Trp), tyrosine (Tyr), and valine (Val) were studied. For that purpose HyperChem 8.0 software was used together with the AM1 method for optimization of the conformation of the molecules in a computer vacuum. Based on the effect of EEF upon the charge density localized at the nitrogen atom of the α-amino group the acids were divided into two groups. They were Group I in which EEF increased the negative charge (Ala, Gly, Ile, Leu, Lys, Met, Phe, Pro, and Thr) and Group II in which EEF induced opposite effect (Cys, Ser, Tyr and Val). Generally, an increase in the EEF strength declined energy and increased dipole moments in non-ionized amino acids and in their inner salt forms. Energy of non-dissociated forms was more negative than these of corresponding zwitterions. Orientation of the molecules in EEF strongly depended on the EEF strength.
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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 | 0.000 | 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 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".