Polarizations for proton knockout reactions from<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mo>∕</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>orbits at<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mn>1</mml:mn><mml:mspace width="0.3em"/><mml:mtext>GeV</mml:mtext></mml:mrow></mml:math>
Bibliographic record
Abstract
The polarization of protons emitted in $(p,2p)$ reactions has been measured for three kinds of targets at $1\phantom{\rule{0.3em}{0ex}}\text{GeV}$. The values of the polarization that we obtain are significantly smaller than the values predicted using the nucleon-nucleon (NN) interaction in free space, and the discrepancy between the two is seen to increase monotonically as a function of the effective mean density, which is defined as a measure of the sensitivity of a reaction to density-dependent terms of the interaction. The experimental data are also compared with a model calculation that includes a relativistic effect, and it is found that inclusion of this effect is able to account for about half of the density-dependent discrepancy between the experimental results and the values predicted with the free space NN interaction. These results, in conjunction with the previous results at $392\phantom{\rule{0.3em}{0ex}}\text{MeV}$, indicate that this discrepancy is not caused by a contribution of multistep processes and provide further evidence that there exists a medium effect.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 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; 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".