Helsinki by nature: The Nature Step to Respiratory Health
Bibliographic record
Abstract
Abstract Background The Nature Step to Respiratory Health was the overarching theme of the 12th General Meeting of the Global Alliance against Chronic Respiratory Diseases (GARD) in Helsinki, August 2018. New approaches are needed to improve respiratory health and reduce premature mortality of chronic diseases by 30% till 2030 (UN Sustainable Development Goals, SDGs). Planetary health is defined as the health of human civilization and the state of the natural systems on which it depends. Planetary health and human health are interconnected, and both need to be considered by individuals and governments while addressing several SDGs. Results The concept of the Nature Step has evolved from innovative research indicating, how changed lifestyle in urban surroundings reduces contact with biodiverse environments, impoverishes microbiota, affects immune regulation and increases risk of NCDs. The Nature Step calls for strengthening connections to nature. Physical activity in natural environments should be promoted, use of fresh vegetables, fruits and water increased, and consumption of sugary drinks, tobacco and alcohol restricted. Nature relatedness should be part of everyday life and especially emphasized in the care of children and the elderly. Taking “nature” to modern cities in a controlled way is possible but a challenge for urban planning, nature conservation, housing, traffic arrangements, energy production, and importantly for supplying and distributing food. Actions against the well-known respiratory risk factors, air pollution and smoking, should be taken simultaneously. Conclusions In Finland and elsewhere in Europe, successful programmes have been implemented to reduce the burden of respiratory disorders and other NCDs. Unhealthy behaviour can be changed by well-coordinated actions involving all stakeholders. The growing public health concern caused by NCDs in urban surroundings cannot be solved by health care alone; a multidisciplinary approach is mandatory.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.011 |
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".