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Record W7028948710

Getting on with Your life with MS: Development, refinement and preliminary testing of a self-management workbook for people living with multiple sclerosis

2017· dissertation· en· W7028948710 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)WorkbookMultiple sclerosisDiseaseTask (project management)Resource (disambiguation)LimitingPresentation (obstetrics)Activities of daily living
DOInot available

Abstract

fetched live from OpenAlex

Individual characteristics of included studies, use of internet and methods of contact with patients.Characteristics of the interventions of the included studies Outcomes of the included studies PEDro evaluation of quality of included studies 4 Source of content for each topic covered Feedback obtained on the individual worksheets content Score on the PEMAT scale for understandability and actionability Examples of participants comments regarding the GETONMS© workbook 7 Content of interviews Presence of Response Shift on the PGI and RS on the then-test Presence of RS and propensity factors for RS by participants Quotes representing each propensity for RS factors 9 Characteristics of persons completing different stages of the study entry process Characteristics of the 23 first participants enrolled in the GETONMS© pilot trial compared with those enrolled in an exercise trial (MSTEP©) using standard clinical recruitment methods Values on the study outcomes from the 23 first participants enrolled into the GETONMS© randomized feasibility study v

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)0.011
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.057
GPT teacher head0.277
Teacher spread0.220 · 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 designNon-randomized trial
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

Citations0
Published2017
Admission routes1
Has abstractyes

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