Imaging mass spectrometry: A new tool for pathology in a molecular age
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
Mass spectrometry (MS) provides unique advantages for the analysis of clinical specimens, and these capabilities have been critical to the advancement of diagnostic medicine. To date, LC-MS is the MS platform most commonly used for diagnostics; however, LC-MS based proteomics is very labor intensive and costly to implement for high volume assays. Furthermore, when analyzing tissue samples, additional laborious sample preparation steps must be employed (e.g. extraction methods or laser microdissection). The direct analysis of cells and tissues by MALDI imaging MS has developed significant momentum for applications that have diagnostic potential. MALDI imaging MS provides molecular information from specific cell types within tissue sections; however, this laser-based approach significantly reduces the analysis time for each location sampled. This Viewpoint discusses the technologies for direct analysis of tissues, the potential for diagnostic applications using MALDI imaging MS, and the challenges faced in the transfer of the technology to the clinical laboratory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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