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Record W2042200902 · doi:10.1177/104990910101800107

The many faces of pain for older, dying adults

2001· review· en· W2042200902 on OpenAlexaff
Margaret C. Gibson, Cori Schroder

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2001
Typereview
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsCanadian Hospice Palliative Care AssociationUniversity of OttawaSt Joseph's Health Care
Fundersnot available
KeywordsMedicinePalliative careGeriatricsDiseasePain controlCognitionPain managementChronic painGerontologyPhysical therapyPsychiatryNursingInternal medicineSurgery

Abstract

fetched live from OpenAlex

An integration of knowledge from the fields of geriatrics, pain management, and palliative care is needed to ensure adequate pain control for the older adult who is dying. An overview is provided of the multiple factors (i.e., chronic illness, malignant disease, care procedures, emotional and cognitive status, response of others) that can cause and exacerbate pain at the end of life for the elderly. Treatment considerations are discussed and an illustrative case study is presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.361
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2001
Admission routes1
Has abstractyes

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