CIVA Modelling Module for Zonal Discrimination Method Part 1-Calibration Block
Why this work is in the frame
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Bibliographic record
Abstract
The 2023 edition of CIVA simulation software has incorporated a module specifically designed for pipeline production weld inspections (Automated Ultrasonic Testing or AUT). Both Zonal Discrimination Method (ZDM) and Total Focussing Method (TFM) options have been included. Unlike the standard ultrasonic module, the “AUT” module has provision to run and display the outputs from multiple channels. This allows for the echo-dynamic display to be seen in a view similar to the strip-chart display commonly used with the zonal discrimination method. Having configured the delay laws to generate an acceptable calibration, CIVA tools such as the meta-model and POD modules can then be used to assess the reliability of the setup (including the efficacy of the calibration block design) for a qualification process. This paper illustrates how the calibration block design is executed for the zonal discrimination method. Results are compared to data collected for a field qualification. A subsequent paper is planned to compare the statistical analysis carried out in the field to assess the inspection reliability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it