Toward improved density functionals for the correlation energy
Bibliographic record
Abstract
Eleven density functionals, including some of the most widely used ones, are tested on their ability to predict nonrelativistic, electron correlation energies for the 17 atoms from He to Ar, the 17 cations from Li(+) to K(+), and 11 (1)S state atoms from Ca to Rn. They all lead to relatively poor predictions for the heavier atoms. Reparametrization of these functionals improves their performance for light atoms but does not alleviate their problems with the heavier, closed-shell atoms. Several novel, few-parameter, density functionals for the correlation energy are developed heuristically. Four new functionals lead to qualitatively improved predictions for the heavier atoms without unreasonably compromising accuracy for the lighter atoms. Further progress would be facilitated by reliable estimates of electron correlation energies for more atoms, particularly heavy ones.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".