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A Psychophysical Investigation of the Facial Action Coding System as an Index of Pain Variability among Older Adults with and without Alzheimer's Disease

2007· article· en· W2025975054 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePain Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Regina
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMedicineCoding (social sciences)DiseaseAudiologyPhysical medicine and rehabilitationInternal medicineStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: Reflexive responses to pain such as facial reactions become increasingly important for pain assessment among patients with Alzheimer's disease (AD) because self-report capabilities diminish as cognitive abilities decline. Our goal was to study facial expressions of pain in patients with and without AD. DESIGN: We employed a quasi-experimental design and used the Facial Action Coding System (FACS) to assess reflexive facial responses to noxious stimuli of varied intensity. Two different modalities of stimulation (mechanical and electrical) were employed. RESULTS: The FACS identified differences in facial expression as a function of level of discomforting stimulation. As expected, there were no significant differences based on disease status (AD vs control group). CONCLUSIONS: This is the first study to discriminate among FACS measures collected during innocuous and graded levels of precisely measured painful stimuli in seniors with (mild) dementia and in healthy control group participants. We conclude that, as hypothesized, FACS can be used for the assessment of evoked pain, regardless of the presence of AD.

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)0.004
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 score0.017
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.016
GPT teacher head0.283
Teacher spread0.267 · 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