Studies of excess heat and convection in a water calorimeter
Bibliographic record
Abstract
To explain a difference of 0.5 % between the absorbed-dose standards of the National Institute of Standards and Technology (NIST) and the National Research Council of Canada (NRCC), Seuntjens et al. suggest the fault lies with the NIST water calorimeter being operated at 22 °C and the method with which the measurements were made. Their calculations show that this difference is due to overprediction of temperature rises of six consecutive (60)Co radiation runs at NIST. However, the consecutive runs they refer to were merely preliminary measurements to determine the procedure for the NIST beam calibration. The beam calibration was determined from only two consecutive runs followed by water circulation to re-establish temperature equilibrium. This procedure was used for measurements on 77 days, with 32 runs per day. Convection external to the glass cylindrical detector assembly performed a beneficial role. It aided (along with conduction) in increasing the rate of excess heat transported away from the thin cylindrical wall. This decreased the rate of heat conducted toward the axially located thermistors. The other sources of excess heat are the: (1) non-water materials in the temperature probe, and (2) exothermic effect of the once-distilled water external to the cylinder. Finite-element calculations were made to determine the separate and combined effects of the excess heat sources for the afterdrift. From this analysis, extrapolation of the measured afterdrifts of two consecutive runs to mid radiation leads to an estimated over-prediction of no more than about 0.1 %. Experimental measurements contradict the calculated results of Seuntjens et al. that convective motion (a plume) originates from the thermistors operated with an electrical power dissipation as low as 0.6 μW, well below the measured threshold of 50 μW. The method used for detecting a plume was sensitive enough to measure a convective plume (if it had started) down to about the 10 μW power level. Measurements also contradict the NRCC calculations in predicting the behavior of the NIST afterdrifts.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".