Bibliographic record
Abstract
In the early 1980s, the X-ray laser program required a new level of understanding and measurements of the atomic physics of highly charged ions. The electron beam ion trap (EBIT) was developed and built at Lawrence Livermore National Laboratory (LLNL) as part of the effort to understand and measure the cross sections and wavelengths of highly charged ions. This paper explains some of the early history of EBIT and how it was used to help develop X-ray lasers. EBIT’s capability was unique and some of the experimental results obtained over the years, related to X-ray lasers, will be shown. As X-ray lasers have now become a table-top tool, new areas of research that involve understanding the index of refraction in partially ionized plasmas will be discussed. In addition, new areas where EBIT may be able to further contribute will be suggested.PACS Nos.: 52.38.–r, 52.25.Os, 52.70.–m, 42.55.Vc, 07.60.Ly, 29.30.Kv, 31.15.–p
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".