Massage Therapy in the Time of COVID-19
Bibliographic record
Abstract
The Journal of Alternative and Complementary MedicineVol. 27, No. 6 Osher CollaborativeMassage Therapy in the Time of COVID-19Carolyn Tague, Dianne Seppelfrick, and Adrien MacKenzieCarolyn TagueAddress correspondence to: Carolyn Tague, MA, CMT, Osher Center for Integrative Medicine, University of California San Francisco, San Francisco, CA 94115, USA E-mail Address: [email protected]Osher Center for Integrative Medicine, University of California San Francisco, San Francisco, CA, USA.Search for more papers by this author, Dianne SeppelfrickOsher Center for Integrative Medicine, Northwestern University, Chicago, IL, USA.Search for more papers by this author, and Adrien MacKenzieOsher Center for Integrative Medicine, Vanderbilt University, Nashville, TN, USA.Search for more papers by this authorPublished Online:16 Jun 2021https://doi.org/10.1089/acm.2021.0045AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byExplaining the Impact of the COVID-19 Pandemic on Massage Therapists in Australia and Canada: A Mixed Methods Study Sarah Fogarty, Phillipa Hay, Felicia Calleri, Lisa Fiddes, Rebecca Barnett, and Amanda Baskwill16 August 2023 | Journal of Integrative and Complementary Medicine, Vol. 0, No. 0Impact of the COVID-19 Pandemic on the Professional Identity of Massage Therapists: The Reporting of a Quantitative Strand of a Mixed-Methods Study Sarah Fogarty, Phillipa Hay, Felicia Calleri, Lisa Fiddes, Rebecca Barnett, and Amanda Baskwill11 February 2022 | Journal of Integrative and Complementary Medicine, Vol. 28, No. 2 Volume 27Issue 6Jun 2021 InformationCopyright 2021, Mary Ann Liebert, Inc., publishersTo cite this article:Carolyn Tague, Dianne Seppelfrick, and Adrien MacKenzie.Massage Therapy in the Time of COVID-19.The Journal of Alternative and Complementary Medicine.Jun 2021.467-472.http://doi.org/10.1089/acm.2021.0045Published in Volume: 27 Issue 6: June 16, 2021Online Ahead of Print:March 31, 2021PDF download
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".