A summary of the Planck constant determinations using the NRC Kibble balance
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Bibliographic record
Abstract
We present a summary of the Planck constant determinations using the NRC watt balance, now referred to as the NRC Kibble balance. The summary includes a reanalysis of the four determinations performed in late 2013, as well as three new determinations performed in 2016. We also present a number of improvements and modifications to the experiment resulting in lower noise and an improved uncertainty analysis. As well, we present a systematic error that had been previously unrecognized and we have quantified its correction. The seven determinations, using three different nominal masses and two different materials, are reanalysed in a manner consistent with that used by the CODATA Task Group on Fundamental Constants (TGFC) and includes a comprehensive assessment of correlations. The result is a Planck constant of 6.626 070 133(60) ×10−34 Js and an inferred value of the Avogadro constant of 6.022 140 772(55) ×1023 mol−1. These fractional uncertainties of less than 10−8 are the smallest published to date.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it