Structured-light 3D Scanning Performance in Offline and In-process Measurement of 3D Printed Parts
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a geometric analysis comparison of structured-light 3D scanners against coordinate measuring machines (CMMs) in measuring 3D printed plastic parts. The resulting geometric analysis of a 3D printed part measured with a contact probe on a CMM and measured with a structured light 3D scanner is presented, along with an error analysis that includes a statistical comparison of the measured geometric deviation. This analysis is then used to determine if structured-light 3D scanners are reliable enough to perform a GD&T analysis of specific features. This paper also presents the results of in-process 3D scanning and compares them to offline 3D scanning to determine the suitability of in-process 3D scanning for comprehensive analysis of geometric deviation and GD&T features.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it