Enhancement of photoacoustic detection of inhomogeneities in polymers
Bibliographic record
Abstract
We report a series of experiments on laser pulsed photoacoustic excitationin turbid polymer samples addressed to evaluate the sound speed in the samples and the presence of inhomogeneities in the bulk. We describe a system which allows the direct measurement of the speed of the detected waves by engraving the surface of the piece under study with a fiduciary pattern of black lines..We also describe how this pattern helps to enhance the sensitivity for the detection of an inhomogeneity in the bulk. These two facts are useful for studies in soft matter systems including, perhaps, biological samples. We have performed an experimental analysis on Grilon® samples in different situations and we show the limitations of the method. Received: 7 December 2012, Accepted: 19 June 2013; Reviewed by: V. Lakshminarayanan, Waterloo University, Canada; Edited by: J. J. Niemela; DOI: http://dx.doi.org/10.4279/PIP.050005Cite as: P. Grondona, H. O. Di Rocco, D. I. Iriarte, J. A. Pomarico, H. F. Ranea-Sandoval, G. M. Bilmes, Papers in Physics 5, 050005 (2013)
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".