The Generalized Energy‐Based Fragmentation Approach with an Improved Fragmentation Scheme: Benchmark Results and Illustrative Applications
Bibliographic record
Abstract
We propose an improved fragmentation scheme for the generalized energy-based fragmentation (GEBF) approach, which improves the accuracy of the GEBF approach in total energy calculations and intermolecular interactions. The main modification is to introduce some two-fragment-centered primitive subsystems, which are neglected in the previous GEBF implementation. Numerical calculations demonstrate that the present GEBF approach can provide more accurate ground-state energies and intermolecular interactions. The present GEBF approach with the M06-2X functional and the cc-pVTZ basis set are employed to investigate the structures and binding energies in two dimeric species, which are related to pseudopolymorphism of a phenyleneethynylene-based π-conjugated molecule. A comparison of the binding free energies in a dimeric species and its corresponding model without C-H···F contacts reveal that the substitution of fluorine atoms weakens the binding of monomers in the dimeric species formed by intermolecular O-H···O hydrogen bonds, but strengthens the binding in the dimer formed by the π-π stacking interaction. Therefore, the C-H···F contacts in these two dimeric species are demonstrated to play a less significant role.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".