Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 217

The DOI matches its Crossref record.

Biological and Analytic Components of Variation in Long-Term Studies of Serum Constituents in Normal Subjects

Williams, George Z, Young, D S, Stein, Mervyn R, Cotlove, Ernest·1970·Clinical Chemistry

Abstract

A study of blood constituents in normal individuals was undertaken to (a) estimate the contribution of biological and analytical factors to the variation of constituents over an extended time period; (b) to explore whether such tests can be used to derive meaningful personal blood "profiles"; and (c) to determine when analytic variation may become large enough to assume medical significance. This first paper describes procedures for subject selection, the laboratory methods employed, and evaluates analytic standard deviations. A group of 68 normal subjects was selected after medical evaluation. Sera were collected and analyzed in duplicate weekly for 10 to 12 weeks. Analytic deviation was estimated from the results of concurrent daily analyses of sterile pools of human serum. Laboratory procedures were introduced to reduce analytic deviation and to allow more accurate estimation of biological components of variation within and among individuals.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/clinchem/16.12.1016

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 217

Metadata

Authors
Williams, G. Z., Young, D. S., Stein, M. R., & Cotlove, E.
Venue
Clinical Chemistry
Published
1970-12-01
Volume
16
Issue
12
Pages
1016-1021
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W2519279601
Cited by
217
References
0
FWCI
13.43
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Biological and Analytic Components of Variation in Long-Term Studies of Serum Constituents in Normal Subjects. https://app.cochat.ai/papers/10.1093/clinchem/16.12.1016
The paper
Williams, G. Z., Young, D. S., Stein, M. R., & Cotlove, E. (1970). Biological and Analytic Components of Variation in Long-Term Studies of Serum Constituents in Normal Subjects. Clinical Chemistry. https://doi.org/10.1093/clinchem/16.12.1016

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.