Stirred-Reactor Coupon Analysis: An International Round Robin Study
Bibliographic record
Abstract
The objective of this task was to determine the precision of the SRCA technique when used to determine the dilute condition corrosion rate. To this end, an interlaboratory round robin study was conducted per the instructions in ASTM Practice E691 to measure the precision with which the SRCA test method can be conducted. Twelve independent labs from eleven different institutions each evaluated four glass compositions in three different conditions. The ASTM procedures recommend at least 6 labs participate in a round robin testing the same 3 materials in the same conditions to determine precision. In this case, 12 labs each performed 12 independent tests. This was only possible thanks to the multi-glass testing capability of the SRCA test. A total of 108 duplicate pairs were used to calculate the repeatability of the tests, with the same glass tested in the same vessel, producing as identical conditions as possible for the replicates. These test results were quite tightly clustered, with a median difference from the average value of the pair of only 2.9%. Based on the calculations outlined in ASTM E177-20 and a measured standard deviation of 4.74%, the intralaboratory repeatability limit (r) was calculated to be within 13.3% of the expected value with 95% confidence level. The reproducibility limit (R) of the test was examined using all 277 data points from the round robin. Because of the differences in dissolution rates due to pH variability and intrinsically for the 12 conditions tested, the reproducibility limits for each condition and overall were calculated from the percent relative residual value for each test. The SRCA test is expected to be reproducible within 64% of the expected value with a 95% confidence level.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".