“Recharging“ Group Electronegativities
Bibliographic record
Abstract
Group electronegativity (gEN) is a fundamental concept of chemistry, relating to acidity, chemical reactivity, activating groups, and protecting groups. Although several empirical and computational methods have been devised for determining gEN, there is no straightforward computational method available to determine these values. We here revisit the determination of gENs using partial charges (“recharging”), computed at a high level of theory using the natural charge of a group (proton, methyl, vinyl, phenyl) bound to the substituent of interest and correlating the values with Pauling electronegativities. The results were found to be in good agreement with previous experimental and computational results. The values also qualitatively reproduced expected electronegativity trends. Furthermore, this work provides the first attempt to compare literature values by scaling them to a single metric (Pauling electronegativities). The method employed is simple and convenient, and could prove to be useful to chemists for determining the gEN of a substituent of interest, or by chemical educators as an assignment or laboratory exercise in a computational chemistry course.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".