Iodine Standard Materials: Preparation and Inter-Laboratory Comparisons
Bibliographic record
Abstract
The Idaho National Laboratory is preparing to enter the community of AMS practioners who analyze for 129Iodine. We expect to take delivery of a 0.5 MV compact accelerator mass spectrometry system, built by NEC, in the early summer of 2014. The primary mission for this instrument is iodine; it is designed to analyze iodine in the +3 charge state. As part of the acceptance testing for this instrument, both at NEC and on-site in our laboratory, some sort of standard or reference material is needed to verify performance. Appropriate standard materials are not readily available in the commercial marketplace. Small quantities can sometimes be acquired from other laboratories already engaged in iodine analyses. In the longer-term, meaningful quantities of standard materials are needed for routine use in analyses, and for quality control functions1. We have prepared some standard materials, starting with elemental Woodward iodine and NIST SRM 3231 [Iodine-129 Isotopic Standard (high level)] 10-6 solution. The goal was to make mixtures at the 5x10-10, 5x10-11, 5x10-12 ratio levels, along with some unmodified Woodward, in the chemical form of silver iodide. Approximately twenty grams of each of these mixtures were prepared. The elemental Woodward iodine was dissolved in chloroform, then reduced to iodide using sodium bisulfite in water. At this point the NIST spike material was added, in the form of sodium iodide. The mixed iodides were oxidized back to iodine in chloroform using hydrogen peroxide. This oxidation step was essential for isotopic equilibration of the 127 and 129 atoms. The iodine was reduced to iodide using sodium bisulfite as before. Excess sulfites and sulfates were precipitated with barium nitrate. After decanting, silver nitrate was used to precipitate the desired silver iodide. Once the silver iodide was produced, the material was kept in darkness as much as possible to minimize photo-oxidation. The various mixtures were synthesized independently of each other; there were no serial dilutions involved. Aliquots of these four materials have been submitted to five established AMS laboratories where iodine analyses are routinely performed: ETH (Zurich), CNA (Seville), PRIME (Purdue), LLNL (California), and Isotrace (Toronto.) Results from four of these laboratories have been received; in general they indicate that the desired 129/127 ratios have been achieved. We will discuss the results of this informal round-robin exercise. If the installation of the instrument in Idaho goes well, we may have some very preliminary results from the new system. An integral part of data reporting is the approach to data reduction. Accordingly, there will also be some discussion of various philosophies of data handling in regard to the use of standards to adjust data, and background subtraction.
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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 | 0.034 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".