Bibliographic record
Abstract
Editorials20 June 2017Alternative Facts Have No Place in ScienceChristine Laine, MD, MPH and Darren B. Taichman, MD, PhDChristine Laine, MD, MPHSearch for more papers by this author and Darren B. Taichman, MD, PhDSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M17-0878 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail On 22 April 2017, scientists and others will take to the streets in more than 300 U.S. locations in a show of support for science (1). The initial impetus for the March for Science seems to have been the Trump administration's characterization of climate change as a hoax. However, current sociopolitics threaten not only climate science but many other scientific disciplines. The politicization of science, in which parties select the knowledge they are willing to pursue and the data they are willing to promote or denigrate, is a peril we must face head-on. Medical science faces particularly dire threats.Climate ...References1. Weinberg C. March for Science. Ann Intern Med. 2017;166:899-900. doi:10.7326/M17-0889 LinkGoogle Scholar2. Crowley RA; Health and Public Policy Committee of the American College of Physicians. Climate change and health: a position paper of the American College of Physicians. Ann Intern Med. 2016;164:608-10. [PMID: 27089232]. doi:10.7326/M15-2766 LinkGoogle Scholar3. Joy EA, Horne BD, Bergstrom S. Addressing air quality and health as a strategy to combat climate change. Ann Intern Med. 2016;164:626-7. [PMID: 27089453]. doi:10.7326/M16-0507 LinkGoogle Scholar4. Bloch EM, Simon MS, Shaz BH. Emerging infections and blood safety in the 21st century. Ann Intern Med. 2016. [PMID: 26974496]. doi:10.7326/M15-1329 LinkGoogle Scholar5. Chou R, Turner JA, Devine EB, Hansen RN, Sullivan SD, Blazina I, et al. The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a National Institutes of Health Pathways to Prevention Workshop. Ann Intern Med. 2015;162:276-86. [PMID: 25581257]. doi:10.7326/M14-2559 LinkGoogle Scholar6. Weinberger SE, Hoyt DB, Lawrence HC, Levin S, Henley DE, Alden ER, et al. Firearm-related injury and death in the United States: a call to action from 8 health professional organizations and the American Bar Association. Ann Intern Med. 2015;162:513-6. [PMID: 25706470]. doi:10.7326/M15-0337 LinkGoogle Scholar7. Anglemyer A, Horvath T, Rutherford G. The accessibility of firearms and risk for suicide and homicide victimization among household members: a systematic review and meta-analysis. Ann Intern Med. 2014;160:101-10. [PMID: 24592495]. doi:10.7326/M13-1301 LinkGoogle Scholar8. Omer SB, Salmon DA, Orenstein WA, deHart MP, Halsey N. Vaccine refusal, mandatory immunization, and the risks of vaccine-preventable diseases. N Engl J Med. 2009;360:1981-8. [PMID: 19420367] doi:10.1056/NEJMsa0806477 CrossrefMedlineGoogle Scholar9. Stephenson AL, Sykes J, Stanojevic S, Quon BS, Marshall BC, Petren K, et al. Survival comparison of patients with cystic fibrosis in Canada and the United States. A population-based cohort study. Ann Intern Med. 2017;166:537-46. doi:10.7326/M16-0858 LinkGoogle Scholar10. Katz IT, Wright AA. Scientific drought, golden eggs, and global leadership—why Trump's NIH funding cuts would be a disaster. N Engl J Med. 2017. doi:10.1056/NEJMp1703734 CrossrefGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M17-0878.Corresponding Author: Christine Laine, MD, MPH, American College of Physicians, 190 N. Independence Mall West, Philadelphia, PA 19106; e-mail, [email protected]org.Current Author Addresses: Drs. Laine and Taichman: American College of Physicians, 190 N. Independence Mall West, Philadelphia, PA 19106.This article was published at Annals.org on 18 April 2017. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoMarch for Science Caroline Weinberg Metrics Cited byCOVID-19 and the eye: alternative facts The 2022 Bowman Club, David L. Easty lectureFacts, Opinions, and Scientific Memes: Reflections of and Recommendations for the March for Science in GermanyThe U.S. Environmental Protection Agency's Proposed Transparency Rule Threatens HealthRenee N. Salas, MD, MPH, MS, Francine Laden, ScD, Wendy B. Jacobs, JD, and Ashish K. Jha, MD, MPHFake news and post-truth pronouncements in general and in early human development 20 June 2017Volume 166, Issue 12Page: 905-906KeywordsCareers in researchClimate changeDisclosureFirearm injuriesForecastingHealth insuranceHealth services researchMortalityResearch laboratoriesVaccines ePublished: 18 April 2017 Issue Published: 20 June 2017 Copyright & PermissionsCopyright © 2017 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 | 0.012 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.069 | 0.026 |
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".