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Record W4416093277 · doi:10.3390/encyclopedia5040190

Visual Analogue Scale

2025· article· en· W4416093277 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

VenueEncyclopedia · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsVisual analogue scaleOrdinal ScaleScale (ratio)Ordinal dataMeasure (data warehouse)Point (geometry)Line (geometry)Level of measurement

Abstract

fetched live from OpenAlex

The Visual Analogue Scale (VAS) is a psychometric instrument used in research and clinical studies to measure the intensity of subjective experiences that cannot be objectively quantified using defined biomarkers, such as pain, fatigue, or mood. It typically consists of a 100 mm straight line with descriptive anchors at each end representing the extremes of the sensation (for example, “no pain” at one end and “the most severe pain imaginable” at the other). Respondents indicate their experience by marking a point on the line, and the distance from the lower anchor is measured and recorded as a continuous variable. VAS data can be analyzed using descriptive or inferential statistics, with the ordinal and non-linear properties of the scale requiring careful justification of the statistical methods applied.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.293
Teacher spread0.288 · 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