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Record W3107261601 · doi:10.3822/ijtmb.v13i4.595

A Research Agenda for the Massage Therapy Profession: a Report from the Massage Therapy Foundation

2020· article· en· W3107261601 on OpenAlexvenueno aff
JoEllen M. Sefton, BSc Jennifer Dexheimer, Niki Munk, Robin Miccio, Ann Blair Kennedy, B. MacDonald, Rob Hemsworth

Bibliographic record

VenueInternational Journal of Therapeutic Massage & Bodywork Research Education & Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMassageFoundation (evidence)Medical educationQuality (philosophy)MedicineAlternative medicinePhysical therapyNursingPsychologyPublic relationsPolitical sciencePathology

Abstract

fetched live from OpenAlex

The Massage Therapy Foundation (MTF) serves as a primary steward of massage therapy research; working to fund and advance the science and art of massage therapy for the entire massage community. The development of an updated research agenda is an essential part of furthering the MTF’s responsibility to help grow the massage therapy knowledge base and increase support for the application of quality research. Integrative health and massage community stakeholders are called upon to help move this MTF 2020 Massage Therapy Research Agenda forward. Together we must strive to continue to advance and disseminate new knowledge to all stakeholders including practitioners, students, instructors, researchers, and policy makers.

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)0.016
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.430
GPT teacher head0.582
Teacher spread0.153 · 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.

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

Citations5
Published2020
Admission routes1
Has abstractyes

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