Correlating MALDI and SIMS imaging mass spectrometric datasets of biological tissue surfaces
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Bibliographic record
Abstract
Abstract Imaging mass spectrometry (IMS) is a rapidly evolving tool for combined chemical and spatial analysis of biological tissues. The complexity of the biological data requires various analytical methods to process the raw datasets. In this article, we report on the ‘semi‐automated’ correlation of two imaging MS datasets obtained with secondary ion mass spectrometry (SIMS) and matrix‐assisted laser desorption/ionization (MALDI) on the same, single brain tissue sample. Prior to statistical analysis, the raw datasets are preprocessed with novel algorithms for baseline correction and peak picking. Principal component analysis (PCA) and canonical correlation analysis (CCA) are used in concert to extract the maximum amount of information about the location of different biochemical molecules on the tissue surface. More importantly, the results show that combining the information from MALDI and SIMS, by using CCA, enables us to correlate and improve the individual results of these two imaging MS experiments. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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) | 0.002 | 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 it