Applications of mass spectrometry in clinical chemistry and biomedical research
Bibliographic record
Abstract
4.5.2Plasma samples 4.6 Capillary liquid chromatography conditions and instrumental settings 4.7 Mass spectrometric analysis 4.8 Quantitation 4.9 Results and discussion 4.9.1 Mass spectrometry of salcatonin 4.9.2Human urine method 4.9.3Human plasma method 4.10 Conclusions 5.0 Mass spectrometric quantitation of C-reactive protein using labelled tryptic peptides 5.1 Connecting text 5.2 Abstract 5.3 5.5 Nephrotoxicity study design and collection of rat urine samples 5.6 Results 5.6.1 Effective in situ digestion of rat urinary CRP 5.6.2Analytical performance 5.6.3Determination of CRP from urinary samples collected from a nephrotoxicity study 5.7 Discussion 5.7.1 Selection of peptides for quantitation 5.7.2 Linear response of digested CRP and purified CRP tryptic peptides 5.8 Conclusions 6.0 Mass spectrometric study and search for posttranslational modifications of human aromatase 6.1 Overview 6.2 1.0
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.
How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".