Evaluating the reproducibility and consistency of different sample preparation techniques used for ATR-FTIR spectroscopy from the RILEM 295-FBB TG1 round robin test
Bibliographic record
Abstract
Abstract Attenuated Total Reflection Fourier Transform Infrared spectroscopy has become a popular spectroscopic technique in bituminous binder analysis. However, comparable results are not obtainable yet due to differences in devices, measurement routines, sample preparation procedures, and spectral evaluation. Thus, the Task Group 1 of the RILEM TC 295-FBB: “Fingerprinting bituminous binders using physicochemical analysis” focuses on bringing this method towards pre-standardization. This study evaluates the reproducibility and consistency from round robin test, where 21 participating laboratories performed six different preparation techniques on three different binders in an unaged, short-term, and long-term aged state. A total of 6461 spectra were recorded and evaluated for their mean, standard deviation and coefficient of variation (CV) in the spectral region between 1800 and 600 cm−1. The results show that the solid sample preparation methods provide excellent reproducibility, with a coefficient of variation below 2%. Only the solvent method showed a higher coefficient of variation at 7.18%. Outliers with a high CV were detected and categorized into two groups: one where only one of the four samples differed and the other where all 16 spectra showed slight scattering in the overall absorption. The consistency of the method is significantly influenced by the accuracy of sample preparation, which is crucial for minimizing differences in slope, baseline, and noise in the spectra. These findings show the excellent reproducibility of these sample preparation methods and will be further examined to establish universal indices for evaluating effects such as ageing, bringing the method closer towards standardization.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".