High resolution pore size analysis in metallic powders by X-ray tomography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The deployment of additive manufacturing processes relies on part quality, specifically the absence of internal defects. Some of those defects have been associated with porosities in the powder feedstock. Since the level of porosity in the powder is generally very low, standard characterisation techniques such as pycnometry and metallography are not suitable for quantification. However, the quantification of such micro sized porosity in metallic powders is crucial to better understand the potential source of internal defects in final components and for quality control purposes. X-ray tomography with a 3 μm resolution offers the possibility to visualise pores in large volume of powder and to quantify their geometrical features and volume fraction using image analysis routines. This combination is unique and demonstrates the power of the approach in comparison to standard powder characterisation techniques. Results presented show the prospects and limits of this technique depending on the imaging device, material and image analysis procedure.
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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 | 0.002 |
| 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 | 0.000 |
| 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