GUM-Style Uncertainty Budget — Sources Combined in Quadrature (.csv)
A five-source uncertainty budget laid out the way the GUM prescribes: each source with its distribution, its divisor, its sensitivity coefficient and its contribution, then the combined and expanded values. Rectangular sources are divided by the square root of three, which is the step budget spreadsheets most often get wrong.
source,value_g,distribution,divisor,sensitivity_coefficient,standard_uncertainty_contribution_g,type
balance repeatability,0.00018,normal,1,1,0.00018,type A
balance resolution,0.00005,rectangular,1.7320508,1,0.00002887,type B
reference mass certificate,0.00012,normal,2,1,0.00006,type B
air buoyancy correction,0.00009,rectangular,1.7320508,1,0.00005196,type B
drift since calibration,0.00007,rectangular,1.7320508,1,0.00004041,type B
combined standard uncertainty,0.00020289,-,-,-,0.00020289,u_c
expanded uncertainty (k=2),0.00040579,-,-,-,0.00040579,U
Specifications
- Sources
- 5
- Columns
- 7
- Combined Standard Uncertainty
- 0.00020289
- Expanded Uncertainty K2
- 0.00040579
- Rectangular Divisor
- sqrt(3) = 1.7320508
- Combination Rule
- root sum of squares
Testing contract
Reference control- Scenario
- Recompute the combined standard uncertainty as the root sum of squares of the contribution column and double it for k=2.
- Expected result
- You get 0.00020289 g combined and 0.00040579 g expanded, and each rectangular source's contribution equals its value divided by the square root of three.
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
How to use this file for testing
“GUM-Style Uncertainty Budget — Sources Combined in Quadrature (.csv)” is a deterministic Novus Examples fixture for Scientific data, CSV parsing, Editor testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: 7 columns. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
Code examples
import pandas as pd
df = pd.read_csv("uncertainty-budget.csv")
print(df.head())
print(df.dtypes)Related files
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