Application of the quantum theory of atoms in molecules to selected physico‐chemical and biophysical problems: Focus on correlation with experiment
Bibliographic record
Abstract
This article reviews how the quantum theory of atoms in molecules (QTAIM) can be used to predict experimental physico-chemical properties of molecules of biologic interest: the amino acids, the polycyclic aromatic hydrocarbons (PAH), and the opiates, for example, morphine and PEO. The predicted experimental properties are as diverse as the partial molar volumes, the free energies of hydration, the second code-letter in the genetic code, the resonance energies, and the proton spin-spin coupling constants. Recent examples of the utilization of QTAIM to construct excellent statistical models (with squared correlation coefficients (r(2)) > 0.9) correlating properties of the electron density and of the pair density to experiment are reviewed. Some new results on the solvent effects on electron delocalization are also presented.
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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".