Generalized Energy-Based Fragmentation CCSD(T)-F12a Method and Application to the Relative Energies of Water Clusters (H<sub>2</sub>O)<sub>20</sub>
Bibliographic record
Abstract
The generalized energy-based fragmentation (GEBF) approach has been implemented for the explicitly correlated F12a of coupled-cluster with the noniterative triples corrections [CCSD(T)-F12a] method for medium- and large-sized systems. By combining the canonical Hartree-Fock (HF) total energies and the GEBF-X correlation energies, the GEBF-X/HF method is illustrated to be more accurate than the origin GEBF-X method, where X could be any electron correlation method, such as second-order Møller-Plesset perturbation theory (MP2), MP2-F12, CCSD(T), and CCSD(T)-F12a. By combining the GEBF-X/HF results at the MP2-F12 and CCSD(T)-F12a levels, we can approximately achieve the CCSD(T) complete basis set (CBS) limit. Our test calculations for 10 low-energy isomers of water 20-mers show that for the relative energies of large water clusters, both the basis set and high-level electron correlation effects should be taken into account, in which the former is even more important. In addition, the GEBF-CCSD(T)/HF method at the CBS limit is used to evaluate 32 levels of density functional theory (DFT) methods. The results show that the DFT methods are difficult to predict the relative energies between the isomers of water 20-mers. The GEBF-CCSD(T)/HF method at the CBS limit is expected to be a benchmark for DFT and other electron correlation methods for medium- and large-sized systems with complex structures, in which both the basis set and electron correlation effects are important.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".