Effects of rescattering in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mi>e</mml:mi><mml:mo>,</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mi>p</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math>reactions within a semiclassical model
Bibliographic record
Abstract
The contribution of rescattering to final state interactions in $(e,{e}^{\ensuremath{'}}p)$ cross sections is studied for medium and high missing energies using a semiclassical model. This approach considers two-step processes that lead to the emission of both nucleons. The effects of nuclear transparency are accounted for in a Glauber-inspired approach and the dispersion effects of the medium at low energies are included. It is found that rescattering is strongly reduced in parallel kinematics. At high missing energies and momenta, the distortion of the short-range correlated tail of the spectral function is dominated by a rearrangement of that strength itself. In perpendicular kinematics, a further enhancement of the experimental yield is due to strength that is originally in the mean field region. This contribution becomes negligible at large missing momenta.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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; both teacher heads agree on what is shown here.
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".