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Record W2031830471 · doi:10.7224/1537-2073-5.4.139

Perceived Effects of Marijuana Use By MS Patients in Saskatchewan—A Pilot Study

2003· article· en· W2031830471 on OpenAlexaffabout
Gary Linassi, Walter Hader

Bibliographic record

VenueInternational Journal of MS Care · 2003
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineDepression (economics)CannabisSpasticityMultiple sclerosisIncidence (geometry)Randomized controlled trialPhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Dissatisfaction with conventional treatments has led to increasing awareness of complementary therapies. To study the use and effects of marijuana in multiple sclerosis (MS), an anonymous questionnaire was sent to 250 randomly selected MS patients from Saskatchewan asking about course of the disease, symptoms, complementary therapy use, and details of past or present marijuana usage. Of the 168 respondents, 36% had smoked marijuana. The incidence of marijuana use for the symptoms of MS was 15%. (A total of 15% used marijuana as treatment for symptoms of MS.) Symptoms that improved included spasticity at sleep onset (58%), weight loss (58%), spasticity when walking (47%), depression (45%), spasms at night (43%), and muscle pain (41%). Statistical significance was not achieved because of the small number of respondents (25 of 168) who smoked marijuana. This small number of cannabis users provides some indication of potential symptomatic relief in MS. The effects of marijuana appear to modestly benefit symptoms of spasticity, pain, and depression. These data support the proposal for a controlled randomized trial to evaluate the beneficial effects of marijuana in MS. (Int J MS Care. 2003; 6: 139–147)

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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

Citations5
Published2003
Admission routes2
Has abstractyes

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