Characterization of zirconium complexes of interest in spent nuclear fuel reprocessing by electrospray ionization mass spectrometry
Bibliographic record
Abstract
Liquid-liquid extraction of zirconium, one of the most important fission products, was followed using electrospray ionization mass spectrometry under conditions simulating reprocessing of nuclear spent fuel. ZrIV can precipitate from the organic phase after extraction by dibutylphosphoric acid (HDBP), the most common degradation product of tributylphosphate (TBP) radiolysis. Different complexes were detected with electrospray used in positive or negative ion modes, according to the extraction conditions such as the ligand/metal ratio. Stoichiometry of the ZrIV complexes was determined by combining isotopic labeling [H15NO3] of the aqueous phase in the extraction system and tandem mass spectrometry experiments. These results were compared with the species observed using other techniques reported in the literature. The mechanisms of ionization/desorption of these complexes are proposed depending on the organic ligand character (neutral (L) such as TBP, or acidic (HL′) such as HDBP), and the ionization mode used. Copyright © 2000 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.001 | 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".