Rheumatology: a close encounter with proteomics
Bibliographic record
Abstract
Proteomics is a fast-growing discipline in biomedicine that can be defined as the large-scale characterization of the entire protein complement of a cell, tissue or organism. Because protein levels and function may be critically dependent upon post-transcriptional mechanisms (e.g. post-translational modifications), there has been significant interest in directly examining protein structure and function. It is now clear that proteomics studies may unmask previously unknown functions of proteins or protein interactions. However, proteomics in the field of rheumatology is still in its infancy. This review guides the reader through the consecutive steps of a proteomics study and provides an outline of the applications in the field of rheumatology, which may range from proteome analyses of biological fluids of rheumatic diseases to identify possible new diagnostic tools, towards more pathophysiological studies on target tissues, such as synovial tissue or articular cartilage. Proteomics has great potential in the field of rheumatology and will no doubt have a great impact on our molecular understanding of these complex diseases.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".