Standard platinum resistance thermometer interpolations in a revised temperature scale
Bibliographic record
Abstract
Abstract The thermal metrology community is considering revising the International Temperature Scale of 1990 (ITS-90), motivated by the opportunity to improve the thermodynamic accuracy, reproducibility, and ease of use of the scale, as well as health and safety concerns with the use of mercury in the current scale. This paper considers the mathematical structure of the standard platinum resistance thermometer (SPRT) interpolations of the ITS-90 and identifies (i) mathematical features that are advantageous and should be retained, (ii) opportunities for improvements, and (iii) the research required to maximise the benefits from such improvements. The improvements considered include minor adjustments that leave ITS-90 intact, numerical adjustments to reference resistance ratios that preserve the structure of ITS-90, fixed-point replacements, new subranges, and large-scale changes in the mathematical structure of the interpolations. A significant research effort will be required to implement some of the changes. Overall, an improvement in the thermodynamic accuracy by a factor of about ten is relatively easily realised, but improvements in reproducibility of the scale of even a couple of tens of percent will be hard won. For most users, the costs and inconvenience of a substantial scale revision may outweigh the benefits.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".