Electron Correlation Functions in Liquids from Scattering Data
Bibliographic record
Abstract
Recent work on the theory of liquid metals has involved correlation functions for the ion–electron density and the electron–electron density. The experimental determination of these functions is discussed for a general homonuclear fluid. It is shown that the electronic correlation functions may be extracted, in principle, by combining X-ray, neutron, and electron scattering data, though the smallness of the differences between the normalized data makes this difficult to do at present. After reviewing the published scattering data, we conclude that the most useful procedure is to compare scattered intensities at a significant reference point, namely the principal maximum of the liquid structure factor. X-ray and neutron data are presented for liquified rare gases, molecular liquids, and liquid metals, and their averages considered. Systematic differences are found between these groups, which prompt the conclusion that electrons in molecular liquids are delocalized by chemical bonding, but that the conducti...
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".