Differentiation of human kidney stones induced by melamine and uric acid using surface desorption atmospheric pressure chemical ionization mass spectrometry
Bibliographic record
Abstract
Clinically obtained human kidney stones of different pathogenesis were dissolved in acetic acid/methanol solutions and then rapidly analyzed by surface desorption atmospheric pressure chemical ionization mass spectrometry (SDAPCI-MS) without any desalination treatment. The mass spectral fingerprints of six groups of kidney stone samples were rapidly recorded in the mass range of m/z 50-400. A set of ten melamine-induced kidney stone samples and nine uric acid derived kidney stone samples were successfully differentiated from other groups by principal component analysis of SDAPCI-MS fingerprints upon positive-ion detection mode. In contrast, the mass spectra recorded using negative-ion detection mode did not give enough information to differentiate those stone samples. The results showed that in addition to the melamine, the chemical compounds enwrapped in the melamine-induced kidney stone samples differed from other kidney stone samples, providing useful hints for studying on the formation mechanisms of melamine-induced kidney stones. This study also provides useful information on establishing a MS-based platform for rapid analysis of the melamine-induced human kidney stones at molecular levels.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one teacher head, 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".