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Record W4294295896 · doi:10.3822/ijtmb.v15i3.713

Massage Therapy: A Person-Centred Approach to Chronic Pain

2022· article· en· W4294295896 on OpenAlexaffvenue
RMT Richard Lebert, Monica Noy, MSc Eric Purves, Jacqueline Tibbett

Bibliographic record

VenueInternational Journal of Therapeutic Massage & Bodywork Research Education & Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsLambton College
Fundersnot available
KeywordsMassageChronic painPsychotherapistMedicinePhysical therapyPain therapyAlternative medicinePsychology

Abstract

fetched live from OpenAlex

Person-centred care is an emergent movement within evidence-based medicine that has the potential to transform the health care system. Person-centred care is a collaborative approach in which health care professionals partner with patients to co-design and deliver personalized care with a focus on physical comfort, emotional well-being, and patient empowerment. By embracing person-centred care through two-way communication, patient engagement, and self-management strategies, massage therapists have the potential to further reduce suffering associated with chronic pain in our society.

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)0.004
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.200
GPT teacher head0.464
Teacher spread0.264 · 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
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

Citations4
Published2022
Admission routes2
Has abstractyes

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