Bibliographic record
Abstract
Although inorganic sulfate is an essential and ubiquitous anion in human biology, it is infrequently assayed in clinical chemistry today. Serum sulfate is difficult to measure accurately without resorting to physicochemical methods, such as ion chromatography, although many other techniques have been described. It is strongly influenced by a variety of physiological factors, including age, diet, pregnancy, and drug ingestion. Urinary excretion is the principal mechanism of disposal for the excess sulfate produced by sulfur amino acid oxidation, and the kidney is the primary site of regulation. In renal failure, sulfoesters accumulate and hypersulfatemia contributes directly to the unmeasured anion gap characteristic of the condition. In contrast, sulfate in urine is readily assayed by a number of means, particularly nephelometry after precipitation as a barium salt. Sulfate is most commonly assayed today as part of the clinical workup for nephrolithiasis, because sulfate is a major contributor to the ionic strength of urine and alters the equilibrium constants governing saturation and precipitation of calcium salts. Total sulfate deficiency has hitherto not been described, although genetic defects in sulfate transporters have been associated recently with congenital osteochondrodystrophies that may be lethal. New insights into sulfate transport and its hormonal regulation may lead to new clinical applications of sulfate analysis in the future.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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".