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Record W2013184334 · doi:10.1002/smr.496

Measurement and quantification are not the same: ISO 15939 and ISO 9126

2010· article· en· W2013184334 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Software Evolution and Process · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMetrologyMeasure (data warehouse)Set (abstract data type)Field (mathematics)Level of measurementComputer scienceUnits of measurementMeasurement uncertaintyScale (ratio)Data miningIndustrial engineeringReliability engineeringSystems engineeringOperations researchMathematicsEngineeringStatisticsGeographyProgramming languagePhysics

Abstract

fetched live from OpenAlex

SUMMARY Measurement based on the international standards for measurement (i.e., metrology) is not the same as judgmental‐based quantification of implicit relationships across a mix of entities and attributes without due consideration of admissible mathematical operations on numbers of different scale types. This paper presents first the Measurement Information Model in ISO 15939 and clarifies next what in it refers to the classical metrology field, and what refers to the quantitative analysis of relationships. The paper concludes with two examples of the designs of a measure for ISO 9126, one focusing on a single attribute and the second attempting to quantify a set of relationships across a number of entities and attributes. Copyright © 2010 John Wiley & Sons, Ltd.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.178
GPT teacher head0.382
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it