Assessment of the Direct Generalized Bloch Approach B0: Application to the Li and Be Atoms and the Molecules LiH, BeH, and the Phenolate Anion
Bibliographic record
Abstract
Besides the necessity of the development of sophisticated methods to calculate correlation energies - be it the coupled-cluster (CC) or the configuration-interaction (CI) methods and their various approaches - one also accentuate the need for efficient and less demanding methods in the area of medium and large molecular systems. Therefore, this article proposes a computational efficient and in our opinion reasonable approach for the calculation of correlation energies for medium and even larger molecules. This approach, named B0, based on the so-called direct generalized Bloch (DGB) equation which has already been successfully applied to small systems. Within those considerations the B0 approach showed promising results so that further investigations are worthwhile. Here, as a further step in the assessment of this method we apply the B0 approach to the Li and Be atoms as well as the LiH and BeH molecules. Molecules which show open and closed shell characteristics in the equilibrium and in the case of dissociation as well. The results are compared with CC and CI and experimental results if available. Since this results are encouraging even when considering small basis sets and with the prospect of larger molecular systems, therefore, we perform also B0 energy calculations for the low-lying states of the phenolate anion which for instance can be used in a simple model of the photoactive yellow protein (PYP) chromophore.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".