Clinical Commentary on an Auricular Marker Associated with COVID-19
Bibliographic record
Abstract
Medical AcupunctureVol. 32, No. 4 CommentaryClinical Commentary on an Auricular Marker Associated with COVID-19Terry Oleson, Richard C. Niemtzow, and Arnyce PockTerry OlesonAddress correspondence to: Terry Oleson, PhD, Auriculotherapy Certification Institute, PMB 270, 8033 Sunset Boulevard, Los Angeles, CA 90046, USA E-mail Address: [email protected]Emperor's College of Traditional Oriental Medicine, Santa Monica, CA, USA.Auriculotherapy Certification Institute, Los Angeles, CA, USA.Search for more papers by this author, Richard C. NiemtzowUnited States Air Force Acupuncture and Integrative Medicine Center, Joint Base Andrews, MD, USA.Search for more papers by this author, and Arnyce PockUniformed Services University of the Health Sciences, Bethesda, MD, USA.Search for more papers by this authorPublished Online:13 Aug 2020https://doi.org/10.1089/acu.2020.29152.comAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail View article"Clinical Commentary on an Auricular Marker Associated with COVID-19." Medical Acupuncture, 32(4), pp. 176–177FiguresReferencesRelatedDetailsCited byThe Role of Acupuncture for Long COVID: Mechanisms and Models James E. Williams and Jacques Moramarco16 June 2022 | Medical Acupuncture, Vol. 34, No. 3 Volume 32Issue 4Aug 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Terry Oleson, Richard C. Niemtzow, and Arnyce Pock.Clinical Commentary on an Auricular Marker Associated with COVID-19.Medical Acupuncture.Aug 2020.176-177.http://doi.org/10.1089/acu.2020.29152.comPublished in Volume: 32 Issue 4: August 13, 2020 TopicsCOVID-19 PDF 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 | 0.007 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.034 | 0.027 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".