Bibliographic record
Abstract
Letters2 May 2006Exercise and Peripheral Arterial DiseaseSteven T. Johnson, MSc and Rhonda C. Bell, PhDSteven T. Johnson, MScFrom University of Alberta, Edmonton, Alberta T6G 2P5, Canada.Search for more papers by this author and Rhonda C. Bell, PhDFrom University of Alberta, Edmonton, Alberta T6G 2P5, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-144-9-200605020-00018 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:The recent article by McDermott and colleagues (1) serves to strengthen the growing body of evidence for the health benefits of regular walking. The authors showed that walking for physical activity at least 3 days per week is not only feasible for patients known to have reduced quality of life (2) because of PAD but can also be self-directed outside of the supervised clinic. The cost savings of this finding have potentially enormous implications that require further economic analysis.The attenuation of functional decline among those who indicated a walking frequency of more than 3 days per ...References1. McDermott MM, Liu K, Ferrucci L, Criqui MH, Greenland P, Guralnik JM, et al. Physical performance in peripheral arterial disease: a slower rate of decline in patients who walk more. Ann Intern Med. 2006;144:10-20. [PMID: 16389250] LinkGoogle Scholar2. Kugler CF, Rudofsky G. Do age and comorbidity affect quality of life or PTA-induced quality-of-life improvements in patients with symptomatic PAD? J Endovasc Ther. 2005;12:387-93. [PMID: 15943516] CrossrefMedlineGoogle Scholar3. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32:S498-504. [PMID: 10993420] CrossrefMedlineGoogle Scholar4. Stevens J, Cai J, Evenson KR, Thomas R. Fitness and fatness as predictors of mortality from all causes and from cardiovascular disease in men and women in the lipid research clinics study. Am J Epidemiol. 2002;156:832-41. [PMID: 12397001] CrossrefMedlineGoogle Scholar5. Johnson ST, Tudor-Locke C, McCargar LJ, Bell RC. Measuring habitual walking speed of people with type 2 diabetes: are they meeting recommendations? Diabetes Care. 2005;28:1503-4. [PMID: 15920080] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From University of Alberta, Edmonton, Alberta T6G 2P5, Canada.Disclosures: None disclosed. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPhysical Performance in Peripheral Arterial Disease: A Slower Rate of Decline in Patients Who Walk More Mary McGrae McDermott , Kiang Liu , Luigi Ferrucci , Michael H. Criqui , Philip Greenland , Jack M. Guralnik , Lu Tian , Joseph R. Schneider , William H. Pearce , Jin Tan , and Gary J. Martin Exercise and Peripheral Arterial Disease Mary M. McDermott , Kiang Liu , and Lu Tian Exercise and Peripheral Arterial Disease Dae Hyun Kim Metrics 2 May 2006Volume 144, Issue 9Page: 699KeywordsExerciseHeart rateMedical risk factorsMorbidityPeripheral vascular diseaseQuality of lifeType 2 diabetesWalking ePublished: 2 May 2006 Issue Published: 2 May 2006 CopyrightCopyright © 2006 by American College of Physicians. All Rights Reserved.PDF DownloadLoading ...
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.104 | 0.025 |
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".