Bibliographic record
Abstract
In their Correspondence, Kamiar Alaei and colleagues (September, 2015)1Alaei K Alaei A Fox A Strengthening US–Iranian relations through public health.Lancet Glob Health. 2015; 3: e525-e526Summary Full Text Full Text PDF Scopus (5) Google Scholar suggest that the Iran–USA relationship could be normalised through academic educational and research collaborations, which has been defined as global health diplomacy. Diplomacy no longer only concerns power, security, and economics, but global challenges such as health. Foreign policies (eg, economic sanctions) can endanger health as well as promote it.2Kickbusch I Global health diplomacy: how foreign policy can influence health.BMJ. 2011; 342: d3154Crossref PubMed Scopus (50) Google Scholar The lifting of economic sanctions could stabilise, steadily driving up all prices including food to some extent, and address the limited availability of high quality drugs and medical devices.3Mohammadi D US-led economic sanctions strangle Iran's drug supply.Lancet. 2013; 381: 279Summary Full Text Full Text PDF PubMed Scopus (22) Google Scholar Sanctions have not only led to material shortages, but have also endangered mental health because of continuous threats. People exposed to stressful life events have higher mortality and morbidity.4Marmot M Wilkinson R Social determinants of health. Oxford University Press, Oxford2005Crossref Scopus (2389) Google Scholar Moreover, research including medical research in Iran has suffered greatly during the international economic sanctions. One of the bibliometric indicators of a country's scientific performance is the number of publications. According to Web of Science, the number of publications by Iranian authors in medical and health sciences has decreased from 23 409 in 2012 to 22 918 in 2013, whereas this number had been steadily increasing in the years before the economic and banking sanctions. In conclusion, the Iran nuclear deal is an opportunity to strengthen the academic and scientific relationship between Iran and the USA and to promote medical research activity and public health especially in Iran. Since Iranian citizens compose the sixth largest group of international practising physicians in the USA,5United States Physician Workforce IssuesFoundation for Advancement of International Medical Education and Research.http://www.faimer.org/research/workforce.htmlDate: 2010Google Scholar and in view of the academic positions that Iranian-Americans hold, their role in a scientific relationship could be prominent.6Aloosh M North America: US sanctions alarm physicians from Iran.Nature. 2015; 522: 419Crossref PubMed Scopus (6) Google Scholar I declare no competing interests.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".