Electron Compton-like quasielastic scattering from H2, D2, and HD
Bibliographic record
Abstract
A significant anomaly in the ratio of the cross sections for quasielastic scattering of D(2) to H(2) in a 50:50 mixture has been reported recently [Phys. Rev. Lett. 100, 043204 (2008)]. In particular, the interpretation of quasielastic scattering provided in that work predicts that the signals should be based on the elemental content and not on the molecular structure, and thus the spectrum for HD and that for the 50:50 mixture should be effectively the same, aside from minor line shape differences. In fact the signal from H in the mixture was low by 31(4)% (or that from D was correspondingly high) when compared to the signal from H in HD. Here, an attempt is made to explain this anomaly by scattering theory calculations based on the first Born and Born-Oppenheimer approximations. The relative contributions of translational, vibrational, and rotational excitations are computed for several temperatures. The computed signals are compared to the experimental spectra of HD and the 50:50 H(2)/D(2) mixture and to pure H(2) and D(2), which were reported previously. Good agreement is found for the spectral line shapes. The predicted peak positions are also found to be in good agreement with experiment except for a slight shift in the case of D(2). However the anomalous cross section ratio of D(2) to H(2) experimentally observed in the 50:50 mixture could not be explained by this approach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".