CCQM-K143 comparison of copper calibration solutions prepared by NMIs/DIs
Bibliographic record
Abstract
Main text CCQM-K143 is a key comparison that assesses participants' ability to prepare single element calibration solutions. Preparing calibration solutions properly is the cornerstone of establishing a traceability link to the International System of Units (SI), and therefore should be tested in order to confirm the validity of CCQM comparisons of more complex materials. CCQM-K143 consisted of participants each preparing a single copper calibration solution at 10 g/kg copper mass fraction and shipping 10 bottled aliquots of that solution to the coordinating laboratory, the National Institute of Standards and Technology (NIST). The masses and mass fraction for the prepared solutions were documented with the submitted samples. The solutions prepared by all participants were measured at NIST by high performance inductively coupled plasma optical emission spectroscopy (HP-ICP-OES). The intensity measurements for copper were not mapped onto values of mass fraction via calibration. Instead, ratios were computed between the measurements for copper and simultaneous measurements for manganese, the internal standard, and all subsequent data reductions, including the computation of the KCRV and the degrees of equivalence, were based on these ratios. Other than for two participants whose measurement results appeared to suffer from calculation or preparation errors, all unilateral degrees of equivalence showed that the measured values did not differ significantly from the KCRV. These results were confirmed by a second set of ICP-OES measurements performed by the Physikalisch-Technische Bundesanstalt (PTB). CCQM-K143 showed that participants are capable of preparing calibration solutions starting from high purity, assayed copper metal. Similar steps are involved when preparing solutions for other elements, so it seems safe to infer that similar capabilities should prevail when preparing many different, single-element solutions. To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ . The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
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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 | 0.028 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.012 |
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".