Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We thank Van Zundert et al1 for their letter elaborating on our recent publication that identified the inaccurate and out-of-date recommendations on preoperative fasting provided in many Internet sources.2 Van Zundert et al1 acknowledge that the Internet includes abundant health-related websites that present incomplete or incorrect data using overly complex language, thus making it difficult for patients to obtain appropriate information. The authors appropriately state that a comprehensive, patient-targeted, open-access, up-to-date Internet resource is needed, and advocate for a “Wiki-Anesthesia” of vetted information. We agree that there is a pressing need to create and promote reliable online sources of medical information; however, previous attempts at “wiki-style” collaboratively edited medical websites have met with mixed success, and many are no longer functional.3 For example, WikiSurgery (www.wikisurgery.com), an initiative supported by the International Journal of Surgery, was launched in 2006, but is no longer functional. AskDrWiki (www.askdrwiki.com) was also launched in 2006, but has experienced poor traffic and has had minimal updates in the past 2 years. Medpedia was a higher-profile website that ceased operations in 2013 after 6 years of existence, despite millions of dollars in funding and support from many top-ranking universities, the American College of Physicians, and the United Kingdom National Health Service.3 Reasons proposed for the lack of success of Medpedia include a paucity of topical breadth, insufficient depth of available topics, and, perhaps most important, poor visibility. Other websites have had modest success, but they are primarily aimed at health care professionals and frequently focus on a single medical specialty (eg, Radiopaedia, WikiDoc, WikEM). A successful patient-directed, health-related website needs to be accurate, understandable, freely accessible, and highly visible. A wiki-type approach has the potential to satisfy all of these features; however, we suggest that Wikipedia itself has the greatest potential for success as the future platform for crowd-sourced information in anesthesiology and other health care areas. Wikipedia is highly visible and already the leading source of health care information for both patients and physicians. Websites on medical topics are generally of moderate to good quality.4 We have searched Wikipedia additionally for information on several topics of interest to patients undergoing anesthesia (Table), finding that these pages are accurate and current; however, they use language that corresponds to a college reading level.Table.: Wikipedia Websites for Selected Anesthesia-Related TopicsThe Wikipedia platform is already reasonably accurate and frequently visited by both patients and physicians, although with room for improvement in readability and gaps in some specific areas of interest to patients (eg, postoperative pain is addressed only briefly within larger and more general text on pain). These relative deficiencies are easily fixed, in part by encouraging greater contribution from experts to identify and address gaps in the current content, with additional editing to ensure appropriate readability for a patient resource. Rather than to add to the vast array of medical websites, we believe we should instead strive to improve upon existing websites such as Wikipedia, which has already established itself as a comprehensive, accurate, and easily accessible Internet resource for many health-related topics. Alana M. Flexman, MDTaren Roughead, BScDepartment of Anesthesiology, Pharmacology,and TherapeuticsUniversity of British ColumbiaBritish Columbia, Canada Jolene H. Fisher, MDDivision of Respirology, Department of MedicineUniversity of TorontoOntario, Canada Darreul Sewell, MBChBDepartment of NeuroanaesthesiaNational Hospital of Neurology and NeurosurgeryUniversity College London HospitalsQueens Square, London, United Kingdom Christopher J. Ryerson, MD, MASDivision of Respirology, Department of Medicine, Centre forHeart Lung Innovation, University of British ColumbiaBritish Columbia, Canada
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it