Discrimination of 1990s Original Automotive Paint Systems: A Collaborative Study of Black Nonmetallic Base Coat/Clear Coat Finishes Using Infrared Spectroscopy
Why this work is in the frame
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Bibliographic record
Abstract
The 1990s saw the introduction of significantly new types of paint binder chemistries into the automotive finish coat market. Considering the pronounced changes in the binders that can now be found in automotive paints and their potential use in a wide variety of finishes worldwide, the Paint Subgroup of the Scientific Working Group for Materials (SWGMAT) initiated a validation study to investigate the ability of commonly accepted methods of forensic paint examination to differentiate between these newer types of paints. Nine automotive paint systems typical of original equipment applications were acquired from General Motors Corporation in 1992. They consisted of steel panels coated with typical electrocoat primers and/or primer surfacers followed by a black nonmetallic base coat and clear coat. The primary purpose of this study was to evaluate the discrimination power of common forensic techniques when applied to the newer generation original automotive finishes. The second purpose was to evaluate interlaboratory reproducibility of automotive paint spectra collected on a variety of Fourier transform infrared (FT-IR) spectrometers and accessories normally used for forensic paint examinations. The results demonstrate that infrared spectroscopy is an effective tool for discriminating between the major automotive paint manufacturers' formulation types which are currently used in original finishes. Furthermore, and equally important, the results illustrate that the mid-infrared spectra of these finishes are generally quite reproducible even when comparing data from different laboratories, commercial FT-IR instruments, and accessories in a "real world," mostly uncontrolled, environment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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