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Record W1963407696 · doi:10.20344/amp.5801

Cancer-Related Pain Management and the Optimal Use of Opioids

2015· review· en· W1963407696 on OpenAlex
Paulo Reis-Pina, Peter G. Lawlor, António Barbosa

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

VenueActa Médica Portuguesa · 2015
Typereview
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsBruyère
FundersUniversidade de LisboaCalouste Gulbenkian Foundation
KeywordsMedicineMedical prescriptionBreakthrough PainPain managementCancer painPillarHealth professionalsCancerHealth careGynecologyPhysical therapyNursingInternal medicine

Abstract

fetched live from OpenAlex

Pain relief is vital to the treatment of cancer. Despite the widespread use and recognition of clinical recommendations for the management of cancer-related pain, avoidable suffering is still prevalent in patients with malignant disease. A gap exists between what is known about pain medical management and actual practices of patients, caregivers, healthcare professionals and institutions. Opioids are the pillar of the medical management of moderate to severe pain. The prescription of opioid analgesics - by a registered medical practitioner for absolute pain control - is a legitimate practice. In this article we look at patients' fears and physicians' general hesitations towards morphine and alike. We examine misconceptions that yield fallacies on the therapeutically use of opioids and, therefore, sustain inadequate pain management.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.059
GPT teacher head0.329
Teacher spread0.269 · 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