Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fusion-energy development has reached an exciting stage with the agreement by seven nations, representing over half the world population, to build the International Thermonuclear Experimental Reactor (ITER) and demonstrate the scientific and technological feasibility of magnetic fusion. High-Z materials such as tungsten are used in plasma-facing components, and contamination of the plasma by sputtered impurities must be controlled to limit radiation losses. Spectroscopic diagnostics will be used to monitor impurity influx and EBIT has played a key role in generating the atomic data necessary to interpret the spectroscopic observations. In this paper, we focus on the key contributions that EBIT devices are uniquely positioned to make in the spectroscopic diagnostics of next-step burning plasmas such as ITER and list specific areas where new data are needed. PACS Nos.: 32.30.Jc, 32.30.Rj, 52.40.Hf, 52.55.Fa, 52.70.Kz, 52.70.La
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.017 | 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 it