Degradation of urine samples and its influence on the <sup>13</sup>C/<sup>12</sup>C ratios of excreted steroids
Bibliographic record
Abstract
The degradation processes in deficiently stored urine samples are well investigated regarding steroid concentrations and diagnostic ratios, such as the quotient of testosterone divided by epitestosterone. In contrast, nothing is known about the influence on carbon isotope ratios (CIR) by inappropriate storage conditions. In general, it is assumed that degradation, i.e. deconjugation or dehydrogenation, does not change CIR and thus CIR can be used in cases where the steroid profile turns out to be invalid. Therefore, the CIR of urinary steroids was investigated in different urine samples during the course of degradation over a time period of six months. Several steroids excreted as glucuronides (androsterone (A), etiocholanolone (E), testosterone, pregnanediol (PD) and 5α- and 5β-androstane-3α,17β-diol) or sulfo-conjugated (A, E and androst-5-ene-3β,17β-diol (5EN17b)) were investigated together with their unconjugated correspondents (A, E, PD and 5EN17b) and the main dehydrogenation products (5α- and 5β-androstane-3,17-dion and androst-4-ene-3,17-dion). For this purpose, the exiting methods for CIR determination were extended and validated. In addition, the urinary concentrations of all investigated steroids were monitored. Particular attention was paid to dehydroepiandrosterone conjugated and unconjugated together with its degradation product 3α,5-cyclo-5α-androstan-6β-ol-17-one as here the strongest influence on CIR was expected.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".