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Record W1608801156 · doi:10.1155/2005/894781

Guidelines for the Use of Cannabinoid Compounds in Chronic Pain

2005· review· en· W1608801156 on OpenAlexaffabout
AJ Clark, ME Lynch, Mark A. Ware, Pierre Beaulieu, I.J. McGilveray, Douglas Gourlay

Bibliographic record

VenuePain Research and Management · 2005
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsCentre for Addiction and Mental HealthUniversity of CalgaryMcGill UniversityUniversity of OttawaDalhousie UniversityUniversité de Montréal
Fundersnot available
KeywordsChronic painCannabisMedicineDosingCannabinoidDronabinolClinical trialRandomized controlled trialMEDLINEPhysical therapyPsychiatryPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide clinicians with guidelines for the use of cannabinoid compounds in the treatment of chronic pain. METHODS: Publications indexed from 1990 to 2005 in the National Library of Medicine Index Medicus were searched through PubMed. A consensus concerning these guidelines was achieved by the authors through review and discussion. RESULTS: There are few clinical trials, case reports or case series concerning the use of cannabinoid compounds in the treatment of chronic pain. There are no randomized clinical trials examining the use of herbal cannabis in the treatment of chronic pain. CONCLUSIONS: A practical approach to the treatment of chronic pain with cannabinoid compounds is presented. Specific suggestions about the off-label dosing of nabilone (Cesamet, Valeant Canada limitee/Limited) and dronabinol (Marinol, Solvay Pharma Inc, Canada) in the treatment of chronic pain are provided.

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)0.019
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.562
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.370
GPT teacher head0.494
Teacher spread0.124 · 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 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

Citations33
Published2005
Admission routes2
Has abstractyes

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