Bibliographic record
Abstract
Mass spectrometry has become the most frequently employed technique in doping control analysis to identify prohibited compounds ever since their use has been banned by international federations. In combination with gas or liquid chromatography and various ionization methods such as electron or chemical ionization, electrospray, atmospheric pressure chemical ionization, atmospheric pressure photo ionization or matrix-assisted laser desorption ionization, numerous applications have been established enabling the sensitive and selective detection of prohibited drugs in matrices such as urine, blood, and hair. The classes of investigated compounds include low molecular weight drugs such as anabolic steroids, diuretics, β2-agonists and β-receptor blocking agents, and others as well as high molecular weight therapeutics, for instance plasma volume expanders based on polysaccharide structures (e.g. hydroxyethyl starch and dextran), hemoglobin-based oxygen therapeutics (e.g. Hemopure), or synthetic insulins. Assays for their identification are commonly based on extractive purification, chemical or enzymatic treatment (i.e. derivatization or degradation) followed by chromatographic and mass spectrometric analysis employing various modern analyzers such as quadrupole, ion trap, triple-quadrupole and magnetic-sector mass spectrometers allowing the sensitive and unambiguous qualitative as well as quantitative determination of xenobiotics in elite athletes doping control samples. Moreover, the administration of drugs naturally occurring in human beings, for instance testosterone, is uncovered by carbon isotope ratio mass spectrometry that enables the differentiation between endogenous and exogenous sources. The comparison of δ-values obtained from endogenously produced steroids independent from testosterone and its metabolism with urinary testosterone and its metabolic products allow the determination of surreptitious applications. Keywords: gas chromatography-nitrogen phosphorus detector analyses, urine matrix, anabolic-androgenic steroids, trimethylsilylation, metabolism, tandem mass spectrometry (ms/ms), testosterone analogues, phase-II-metabolites, isotope ratio mass spectrometry, diuretic
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".