Characteristics of the total disintegration events of emulsion heavy target nuclei caused by O<sup>16</sup> and <sup>28</sup>Si nuclei at high energies
Bibliographic record
Abstract
The present paper deals with the interactions of 16O and 28Si nuclei with emulsion heavy target nuclei (silver (Ag) and bromine (Br)) at 4.5A GeV/c. The results have been analyzed to identify interesting characteristics of the total disintegration (TD) events produced in these interactions. Events having a number of heavily ionizing particles Nh ≥ 28 have been selected in this study. The integral multiplicity distributions for the disintegrated particles from the target nuclei have been used to separate the inelastic interactions with the free hydrogen (H), the light (CNO), and the heavy (AgBr) nuclei. The average multiplicities of the different secondary particles emitted in these interactions have been compared with the corresponding ones of different projectiles nearly at the same momentum. The average multiplicity of the grey particles is found to increase with the mass of the projectile, while the average multiplicity of the black particles is found to decrease with increasing mass of the projectile; this result agrees with the prediction of the fireball model. Also, the dependence of the shower, grey, and black particles produced in the TD events on the mass of the projectile has been studied. Moreover, the dependence of the probability of the TD for the projectile mass as well as the target fragments has also been discussed. The results show that the multiplicity distributions of the shower, grey, and black particles present a Gaussian distribution. Finally, the linear dependence of the grey and compound multiplicities on the black, heavy, and shower particles has also been observed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".