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Record W2063397970 · doi:10.1177/1049909108322293

Word Choices of Advanced Cancer Patients: Frequency of Nociceptive and Neuropathic Pain

2008· article· en· W2063397970 on OpenAlexfundaboutno aff
Marjorie C. Dobratz

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2008
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineNociceptionNeuropathic painMcGill Pain QuestionnaireCancerCancer painPhysical therapyAnesthesiaInternal medicineVisual analogue scale

Abstract

fetched live from OpenAlex

The purpose of this study was to determine if nociceptive and/or neuropathic pain in advanced cancer patients could be identified by word selections made on the McGill Melzack Pain Questionnaire. Theoretical definitions for nociceptive and neuropathic pain provided a framework for categorizing the word descriptors in the McGill Melzack Pain Questionnaire's sensory and miscellaneous dimensions. A description study design was used to group word frequencies by primary site and pain type. The participants were 76 advanced cancer patients who received home-based hospice services. A wide range of word choices for lung cancer patients supported both nociceptive and neuropathic pain. Individuals with colon and liver cancer selected words that described 2 types of nociceptive (visceral, somatic) pain, while those with prostate cancer noted somatic pain. A set frequency was not reached by individuals with breast, pancreatic, gastric, and other advanced cancers. This study provided evidence that advanced cancer patients select words that describe nociceptive and neuropathic pain types.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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 score0.060
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2008
Admission routes2
Has abstractyes

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