An IAEA multi-technique X-ray spectrometry endstation at Elettra Sincrotrone Trieste: benchmarking results and interdisciplinary applications
Bibliographic record
Abstract
The International Atomic Energy Agency (IAEA) jointly with the Elettra Sincrotrone Trieste (EST) operates a multipurpose X-ray spectrometry endstation at the X-ray Fluorescence beamline (10.1L). The facility has been available to external users since the beginning of 2015 through the peer-review process of EST. Using this collaboration framework, the IAEA supports and promotes synchrotron-radiation-based research and training activities for various research groups from the IAEA Member States, especially those who have limited previous experience and resources to access a synchrotron radiation facility. This paper aims to provide a broad overview about various analytical capabilities, intrinsic features and performance figures of the IAEA X-ray spectrometry endstation through the measured results. The IAEA-EST endstation works with monochromatic X-rays in the energy range 3.7-14 keV for the Elettra storage ring operating at 2.0 or 2.4 GeV electron energy. It offers a combination of different advanced analytical probes, e.g. X-ray reflectivity, X-ray absorption fine-structure measurements, grazing-incidence X-ray fluorescence measurements, using different excitation and detection geometries, and thereby supports a comprehensive characterization for different kinds of nanostructured and bulk materials.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".